﻿* Encoding: UTF-8.


***********REPLICATION - ADDICTION TO SURVEYS
 
**2012 DATA

GET 
  FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/ANES 2012/Base File/anes_timeseries_2012.sav'. 
 ALTER TYPE ALL(A=AMIN).
DATASET NAME DataSet1 WINDOW=FRONT.

*2012 RECONTACT

GET 
  FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/ANES 2012/anes_panel_2013_inetrecontact.sav'. 
DATASET NAME DataSet2 WINDOW=FRONT.

DELETE VARIABLES version.
EXE.

COMPUTE Reinterview2=1.
EXECUTE.

DATASET ACTIVATE DataSet1.
STAR JOIN
  /SELECT *
  /FROM * AS t0
  /JOIN 'DataSet2' AS t1
    ON t0.caseid=t1.caseid
  /OUTFILE FILE=*.

DATASET CLOSE DataSet2.
EXE.

COMPUTE Reinterview=0.
IF (Reinterview2=1) Reinterview =1.
Freq Reinterview.

********CLEANING DATA

***MODEL VARIABLES

*WEIGHTS

DESCRIPTIVES weight_ftf weight_web weight_full.

WEIGHT BY weight_web.

Freq wave_completions.
Freq mode.

**MAIN INDEPENDENT VARIABLE

Freq profile_surveyscompleted.
MISSING VALUES profile_surveyscompleted (-1).
Freq profile_surveyscompleted.
COMPUTE NumberSurveys = profile_surveyscompleted.
Freq NumberSurveys.

Freq profile_panelentrydate.
STRING ProfileStartYear (A4).
STRING ProfileStartMonth ProfileStartDay (A2).
EXE.
COMPUTE ProfileStartYear = substr(profile_panelentrydate,1,4).
COMPUTE ProfileStartMonth = substr(profile_panelentrydate,5,2).
COMPUTE ProfileStartDay = substr(profile_panelentrydate,7,2).
ALTER TYPE ProfileStartYear (F4).
ALTER TYPE ProfileStartMonth ProfileStartDay (F2).
Freq ProfileStartYear ProfileStartMonth ProfileStartDay.

* Date and Time Wizard: PanelStartDate.
COMPUTE  PanelStartDate=DATE.DMY(ProfileStartDay, ProfileStartMonth, ProfileStartYear).
VARIABLE LABELS  PanelStartDate "".
VARIABLE LEVEL  PanelStartDate (SCALE).
FORMATS  PanelStartDate (ADATE10).
VARIABLE WIDTH  PanelStartDate(10).
EXECUTE.

STRING Oct102012 (A10).
COMPUTE Oct102012 = '10/10/2012'.
ALTER TYPE Oct102012 (ADATE10).
Freq Oct102012.

* Date and Time Wizard: PanelStartToEDSurveyDays.
COMPUTE  DaysInPanel=DATEDIF(Oct102012, PanelStartDate, "days").
VARIABLE LABELS  DaysInPanel.
VARIABLE LEVEL  DaysInPanel (SCALE).
FORMATS  DaysInPanel (F5.0).
VARIABLE WIDTH  DaysInPanel(5).
EXECUTE.
DESCRIPTIVES DaysInPanel.

COMPUTE MonthsInPanel = DaysInPanel/30.
DESCRIPTIVES MonthsInPanel.


COMPUTE NumberSurveysPerMonth = NumberSurveys/MonthsInPanel.
DESCRIPTIVES NumberSurveysPerMonth.

*DESCRIPTIVES TABLES

Freq  NumberSurveys MonthsInPanel NumberSurveysPerMonth
    /format=notable
    /stats = mean stdev median min max.

CORR  NumberSurveys MonthsInPanel NumberSurveysPerMonth.

***CONTROL VARIABLES


Freq gender_respondent_x.
RECODE gender_respondent_x (1=0) (2=1) INTO female.
Freq female.

Freq dem_age_r_x.
COMPUTE age = dem_age_r_x.
MISSING VALUES age (-2).
Freq age.
RECODE age (17 THRU 30=1) (31 THRU 45 =2) (46 THRU 60 = 3) (61 THRU HI = 4) INTO agecats. 
Freq agecats.
VALUE LABELS
agecats
1 ' 18-30'
2 '31-45'
3 '46-60'
4 '61+'.
Freq agecats

Freq dem_marital.
RECODE dem_marital (1 THRU 2 = 1) (3=2) (4=3) (5=4) (6=5) INTO maritalstatus.
VALUE LABELS
maritalstatus
1 'Married'
2 'Widowed'
3 'Divorced'
4 'Separated'
5 'Never married'.
Freq maritalstatus.
RECODE maritalstatus (1=1) (2 THRU 5=0) INTO married.
Freq married.

Freq dem_edugroup_x.
COMPUTE educ = dem_edugroup_x.
MISSING VALUES educ (-9, -2).
VALUE LABELS
educ
1 'LT HS'
2 'HS credential'
3 'Some post-high school'
4 'Bachelors degree'
5 'Graduate degree'.
Freq educ.

Freq dem_empstatus_1digitfin_x.
RECODE dem_empstatus_1digitfin_x (1=1) (2 THRU 4=2) (5=3) (6=4) (7=5) (8=6) INTO employment.
VALUE LABELS 
employment
1 'Working gt 20 hrs/wk'
2 'Unemployed'
3 'Retired'
4 'Permanently disabled'
5 'Homemaker'
6 'Student'.
Freq employment.

RECODE employment (1=1) (2 THRU 6 = 0) INTO Working.
Freq Working. 

RECODE employment (1=1) (2 THRU 6 = 0) INTO WorkingGT20Hours.
Freq WorkingGT20Hours.
RECODE employment (1=0) (2 =1) (3 THRU 6 = 0) INTO WUnemployed.
RECODE employment (1 THRU 2 =0) (3 =1) (4 THRU 6 = 0) INTO WRetired.
RECODE employment (1 THRU 3 =0) (4 =1) (5 THRU 6 = 0) INTO WPermanentlyDisabled.
RECODE employment (1 THRU 4 =0) (5 =1) (5 THRU 6 = 0) INTO WHomemaker.
RECODE employment (1 THRU 5 =0) (6 =1)  INTO WStudent.
Freq WorkingGT20Hours WUnemployed WRetired WPermanentlyDisabled WHomemaker WStudent.

Freq  dem_raceeth_x.
COMPUTE raceethnic = dem_raceeth_x.
VALUE LABELS
raceethnic 
1 'White'
2 'Black'
3 'Asian'
4 'Native'
5 'Hispanic'
6 'Other'.
MISSING VALUES raceethnic (-9).
Freq raceethnic.
RECODE raceethnic (1=1) (2 THRU 6 = 0) INTO white.
Freq white.
ONEWAY NumberSurveys BY raceethnic
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

Freq dem2_inethome.
RECODE dem2_inethome (1=1) (2=0) INTO Internet.
VALUE LABELS
Internet
0 'No'
1 'Yes'.
Freq Internet.
T-TEST GROUPS= Internet(0 1) 
  /MISSING=ANALYSIS 
  /VARIABLES=NumberSurveys
  /CRITERIA=CI(.95).

Freq dem2_landline dem2_cellnum.
RECODE dem2_landline dem2_cellnum (0=0) (1 THRU HI = 1) INTO HHLandline HHCellphone.
VALUE LABELS 
HHLandline HHCellphone
0 'No'
1 'Yes'.
Freq HHLandline HHCellphone.
T-TEST GROUPS=HHLandline(0 1) 
  /MISSING=ANALYSIS 
  /VARIABLES=NumberSurveys
  /CRITERIA=CI(.95).
T-TEST GROUPS= HHCellphone(0 1) 
  /MISSING=ANALYSIS 
  /VARIABLES=NumberSurveys
  /CRITERIA=CI(.95).

Freq inc_incgroup_pre incgroup_prepost_x.
COMPUTE incomePre = inc_incgroup_pre.
COMPUTE incomePost = incgroup_prepost_x.
VALUE LABELS
incomePre incomePost
1 '<5K'
2 '5-10'
3 '10-12.5'
4 '12.5-15'
5 '15-17.5'
6 '17.5-20'
7 '20-22.5'
8 '22.5-25'
9 '25-27.5'
10 '27.5-30'
11 '30-35'
12 '35-40'
13 '40-45'
14 '45-50'
15 '50-55'
16 '55-60'
17 '60-65'
18 '65-70'
19 '70-75'
20 '75-80'
21 '80-90'
22 '90-100'
23 '100-110'
24 '110-125'
25 '125-150'
26 '150-175'
27 '175-250'
28 '>250'.
MISSING VALUES incomePre incomePost (-9, -8, -2).
Freq incomePre incomePost.
RECODE incomePre (1 THRU 10=1) (11 THRU 16=2) (17 THRU 22 = 3) (23 THRU HI = 4) INTO incomepretrunc.
VALUE LABELS 
incomepretrunc
1 '0-29.9k'
2 '30-59.9k'
3 '60-99.9k'
4 '100+k'.
Freq incomepretrunc.

Freq pid_x.
MISSING VALUES pid_x (-2).
RECODE pid_x (1 THRU 3 = 1) (4=2) (5 THRU 7 =3) INTO pid3.
VALUE LABELS
pid3
1 'Democrat'
2 'Independent'
3 'Republican'.
RECODE pid_x (1 THRU 3 =1) (4 THRU 7 =0) INTO Dem.
RECODE pid_x (1 THRU 3 =0) (4=1) (5 THRU 7 =0) INTO Indep.
RECODE pid_x (1 THRU 4 =0) (5 THRU 7 =1) INTO Rep.
Freq Dem Indep Rep pid_x.

Freq libcpre_self.
MISSING VALUES libcpre_self (-9,-8,-2).
Freq libcpre_self.
RECODE libcpre_self (1 THRU 3 =1) (4=2) (5 THRU 7 = 3) INTO libcon3.
VALUE LABELS 
libcon3 
1 'Liberal'
2 'Moderate'
3 'Conservative'.
Freq libcon3.
RECODE libcon3 (1=1) (2=0) (3=0) INTO Lib.
RECODE libcon3 (1=0) (2=1) (3=0) INTO Mod.
RECODE libcon3 (1=0) (2=0) (3=1) INTO Cons.
Freq Lib Mod Cons.

Freq interest_attention.
MISSING VALUES interest_attention (-9, -8).
RECODE interest_attention (1=5) (2=4) (3=3) (4=2) (5=1) INTO InterestPolitics.
VALUE LABELS
InterestPolitics
1 'Never'
2 'Some'
3 'About half'
4 'Most times'
5 'Always'.
Freq InterestPolitics.

****TABLE 1. TOTAL NUMBER OF SURVEYS

WEIGHT BY weight_web.
EXE.
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

Freq female agecats married raceethnic educ.

TEMP. 
SELECT IF (female = 1).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (female=0).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (agecats =1).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (agecats =2).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (agecats =3).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (agecats =4).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (raceethnic =1).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (raceethnic =2).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (raceethnic =5).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (raceethnic =3).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (educ =1).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (educ =2).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (educ =3).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (educ =4).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.

TEMP.
SELECT IF (educ =5).
Freq  NumberSurveys 
    /format=notable
    /stats = mean stdev median min max.


WEIGHT BY c5_weight.
EXE.
COMPUTE RecontactNumberSurveys = C5_num_comp.
Freq  RecontactNumberSurveys  
    /format=notable
    /stats = mean stdev median min max.

****TABLE 2. DETERMINANTS OF TOTAL NUMBER OF SURVEYS COMPLETED

*2012

WEIGHT BY weight_web.
EXE.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT NumberSurveys 
  /METHOD=ENTER  female agecats married educ working white Internet HHLandline incomePre Indep Rep  Mod Cons.

WEIGHT BY c5_weight.
EXE.
TEMP.
SELECT IF (Reinterview=1).
REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT NumberSurveys 
  /METHOD=ENTER  female agecats married educ working white Internet HHLandline incomePre Indep Rep  Mod Cons.

*2013

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT RecontactNumberSurveys 
  /METHOD=ENTER  female agecats married educ working white Internet HHLandline incomePre Indep Rep  Mod Cons.

WEIGHT BY c5_weight.
EXE.
COMPUTE Difference = RecontactNumberSurveys-NumberSurveys.
DESCRIPTIVES Difference.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT Difference 
  /METHOD=ENTER  female agecats married educ working white Internet HHLandline incomePre Indep Rep  Mod Cons.

****TABLE 3. SURVEY DURATION

WEIGHT BY weight_web.
EXECUTE.

DESCRIPTIVES admin_pre_iwlength.
EXE.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT admin_pre_iwlength
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep  Mod Cons.

WEIGHT BY c5_weight.
EXECUTE.

DESCRIPTIVES C5_duration.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT C5_duration
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep  Mod Cons.

****TABLE 4. NON-DIFFERENTIATION

WEIGHT BY weight_web.
EXECUTE.

***ND 1: MEDIA DAYS NON-DIFFERENTIATION

Freq prmedia_wkinews  prmedia_wktvnws prmedia_wkpaprnws  prmedia_wkrdnws .
MISSING VALUES prmedia_wkinews  prmedia_wktvnws prmedia_wkpaprnws  prmedia_wkrdnws (-9 THRU -1).
Freq prmedia_wkinews  prmedia_wktvnws prmedia_wkpaprnws  prmedia_wkrdnws .
COMPUTE nd1a = prmedia_wkinews.
COMPUTE nd1b = prmedia_wktvnws.
COMPUTE nd1c = prmedia_wkpaprnws.
COMPUTE nd1d =      prmedia_wkrdnws.
Freq nd1a nd1b nd1c nd1d.

COMPUTE nd1mediadays = 
(
(sqrt(abs(nd1a - nd1b))) + 
(sqrt(abs(nd1a - nd1c))) + 
(sqrt(abs(nd1a - nd1d))) + 
(sqrt(abs(nd1b - nd1c))) + 
(sqrt(abs(nd1b - nd1d))) + 
(sqrt(abs(nd1c - nd1d)))
/4).
DESCRIPTIVES nd1mediadays.
COMPUTE STDnd1mediadays = abs(1- (nd1mediadays/11.19)).
DESCRIPTIVES STDnd1mediadays.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd1mediadays
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 2: MEDIA ATTENTION  NON-DIFFERENTIATION

Freq prmedia_atinews prmedia_attvnews prmedia_atpprnews prmedia_atrdnews.
RECODE prmedia_atinews prmedia_attvnews prmedia_atpprnews prmedia_atrdnews (1=5) (2=4) (3=3) 
(4=2) (5=1) INTO prmedia_atinewsRC prmedia_attvnewsRC prmedia_atpprnewsRC prmedia_atrdnewsRC.
VALUE LABELS 
prmedia_atinewsRC prmedia_attvnewsRC prmedia_atpprnewsRC prmedia_atrdnewsRC
1 'None at all'
2 'A little'
3 'A moderate amount'
4 'A lot'
5 'A great deal'.
Freq prmedia_atinewsRC prmedia_attvnewsRC prmedia_atpprnewsRC prmedia_atrdnewsRC.
Freq prmedia_atinewsRC prmedia_attvnewsRC prmedia_atpprnewsRC prmedia_atrdnewsRC .
COMPUTE nd2a = prmedia_atinewsRC.
COMPUTE nd2b = prmedia_attvnewsRC.
COMPUTE nd2c = prmedia_atpprnewsRC.
COMPUTE nd2d =      prmedia_atrdnewsRC.
Freq nd2a nd2b nd2c nd2d.

COMPUTE nd2mediaatt = 
(
(sqrt(abs(nd2a - nd2b))) + 
(sqrt(abs(nd2a - nd2c))) + 
(sqrt(abs(nd2a - nd2d))) + 
(sqrt(abs(nd2b - nd2c))) + 
(sqrt(abs(nd2b - nd2d))) + 
(sqrt(abs(nd2c - nd2d)))
/4).
DESCRIPTIVES nd2mediaatt.
COMPUTE STDnd2mediaatt = abs(1- (nd2mediaatt/7.82)).
DESCRIPTIVES STDnd2mediaatt.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd2mediaatt
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 3: CANDIDATE LIKES  NON-DIFFERENTIATION

Freq candlik_likedpc  candlik_disldpc candlik_likerpc  candlik_dislrpc .
MISSING VALUES candlik_likedpc  candlik_disldpc candlik_likerpc  candlik_dislrpc (-9,-8).
RECODE candlik_likedpc  candlik_disldpc candlik_likerpc  candlik_dislrpc (1=1) (2=0)
INTO candlik_likedpcRC  candlik_disldpcRC candlik_likerpcRC  candlik_dislrpcRC.
VALUE LABELS
candlik_likedpcRC  candlik_disldpcRC candlik_likerpcRC  candlik_dislrpcRC
0 'No'
1 'Yes'.
Freq candlik_likedpcRC  candlik_disldpcRC candlik_likerpcRC  candlik_dislrpcRC.
Freq candlik_likedpcRC  candlik_disldpcRC candlik_likerpcRC  candlik_dislrpcRC .
COMPUTE nd3a = candlik_likedpcRC.
COMPUTE nd3b = candlik_disldpcRC.
COMPUTE nd3c = candlik_likerpcRC.
COMPUTE nd3d =      candlik_dislrpcRC.
Freq nd3a nd3b nd3c nd3d.

COMPUTE nd3candlikes = 
(
(sqrt(abs(nd3a - nd3b))) + 
(sqrt(abs(nd3a - nd3c))) + 
(sqrt(abs(nd3a - nd3d))) + 
(sqrt(abs(nd3b - nd3c))) + 
(sqrt(abs(nd3b - nd3d))) + 
(sqrt(abs(nd3c - nd3d)))
/4).
DESCRIPTIVES nd3candlikes.
COMPUTE STDnd3candlikes = abs(1- (nd3candlikes/4)).
DESCRIPTIVES STDnd3candlikes.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd3candlikes
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 4: PRES APPROVAL MEASURES  NON-DIFFERENTIATION

Freq presapp_job_x presapp_econ_x presapp_foreign_x presapp_health_x presapp_war_x.
RECODE presapp_job_x presapp_econ_x presapp_foreign_x presapp_health_x presapp_war_x
(1=4) (2=3)  (4=2) (5=1) INTO PresAppJob PresAppEcon PresAppForeign PresAppHealth PresAppWar.
VALUE LABELS
PresAppJob PresAppEcon PresAppForeign PresAppHealth PresAppWar
1 'Disapprove strongly'
2 'Disapprove'
3 'Approve'
4 'Approve stongly'.
Freq PresAppJob PresAppEcon PresAppForeign PresAppHealth PresAppWar.
Freq PresAppJob PresAppEcon PresAppForeign PresAppHealth PresAppWar.
COMPUTE nd4a = PresAppJob.
COMPUTE nd4b = PresAppEcon.
COMPUTE nd4c = PresAppForeign.
COMPUTE nd4d =      PresAppHealth.
COMPUTE nd4e =      PresAppWar.
Freq nd4a nd4b nd4c nd4d nd4e.

COMPUTE nd4presappr = 
(
(sqrt(abs(nd4a - nd4b))) + 
(sqrt(abs(nd4a - nd4c))) + 
(sqrt(abs(nd4a - nd4d))) + 
(sqrt(abs(nd4a - nd4e))) + 
(sqrt(abs(nd4b - nd4c))) + 
(sqrt(abs(nd4b - nd4d))) + 
(sqrt(abs(nd4b - nd4e))) + 
(sqrt(abs(nd4c - nd4d))) +
(sqrt(abs(nd4c - nd4e))) +
(sqrt(abs(nd4d - nd4e)))
/5).
DESCRIPTIVES nd4presappr.
COMPUTE STDnd4presappr = abs(1- (nd4presappr/11.76)).
DESCRIPTIVES STDnd4presappr.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd4presappr
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 5: THERMS

Freq ft_dpc ft_rpc ft_dvpc ft_rvpc ft_hclinton ft_gwb ft_dem ft_rep.
MISSING VALUES ft_dpc ft_rpc ft_dvpc ft_rvpc ft_hclinton ft_gwb ft_dem ft_rep (-9, -8,-2).
Freq ft_dpc ft_rpc ft_dvpc ft_rvpc ft_hclinton ft_gwb ft_dem ft_rep.
COMPUTE nd5a = ft_dpc.
COMPUTE nd5b = ft_rpc.
COMPUTE nd5c = ft_dvpc.
COMPUTE nd5d =      ft_rvpc.
COMPUTE nd5e =      ft_hclinton.
COMPUTE nd5f =      ft_gwb.
COMPUTE nd5g =      ft_dem.
COMPUTE nd5h =      ft_rep.
DESCRIPTIVES nd5a nd5b nd5c nd5d nd5e nd5f nd5g nd5h.

COMPUTE nd5therms = 
(
(sqrt(abs(nd5a - nd5b))) + 
(sqrt(abs(nd5a - nd5c))) + 
(sqrt(abs(nd5a - nd5d))) + 
(sqrt(abs(nd5a - nd5e))) + 
(sqrt(abs(nd5a - nd5f))) + 
(sqrt(abs(nd5a - nd5g))) + 
(sqrt(abs(nd5a - nd5h))) + 
(sqrt(abs(nd5b - nd5c))) + 
(sqrt(abs(nd5b - nd5d))) + 
(sqrt(abs(nd5b - nd5e))) + 
(sqrt(abs(nd5b - nd5f))) + 
(sqrt(abs(nd5b - nd5g))) + 
(sqrt(abs(nd5b - nd5h))) + 
(sqrt(abs(nd5c - nd5d))) +
(sqrt(abs(nd5c - nd5e))) +
(sqrt(abs(nd5c - nd5f))) +
(sqrt(abs(nd5c - nd5g))) +
(sqrt(abs(nd5c - nd5h))) +
(sqrt(abs(nd5d - nd5e))) +
(sqrt(abs(nd5d - nd5f))) +
(sqrt(abs(nd5d - nd5g))) +
(sqrt(abs(nd5d - nd5h))) +
(sqrt(abs(nd5e - nd5f))) +
(sqrt(abs(nd5e - nd5g))) +
(sqrt(abs(nd5e - nd5h))) +
(sqrt(abs(nd5f - nd5g))) +
(sqrt(abs(nd5f - nd5h))) +
(sqrt(abs(nd5g - nd5h)))
/8).
DESCRIPTIVES nd5therms.
COMPUTE STDnd5therms = abs(1- (nd5therms/181.63)).
DESCRIPTIVES STDnd5therms.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd5therms
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 6 PARTY LIKES  NON-DIFFERENTIATION

Freq ptylik_likdp ptylik_disldp ptylik_likrp ptylik_dislrp.
RECODE ptylik_likdp ptylik_disldp ptylik_likrp ptylik_dislrp (1=1) (2=0) INTO
LikeDem DisLikeDem LikeRep DisLikeRep.
Freq LikeDem DisLikeDem LikeRep DisLikeRep.
Freq LikeDem DisLikeDem LikeRep DisLikeRep.
COMPUTE nd6a = LikeDem.
COMPUTE nd6b = DisLikeDem.
COMPUTE nd6c = LikeRep.
COMPUTE nd6d =      DisLikeRep.
Freq nd6a nd6b nd6c nd6d.

COMPUTE nd6partlikes = 
(
(sqrt(abs(nd6a - nd6b))) + 
(sqrt(abs(nd6a - nd6c))) + 
(sqrt(abs(nd6a - nd6d))) + 
(sqrt(abs(nd6b - nd6c))) + 
(sqrt(abs(nd6b - nd6d))) + 
(sqrt(abs(nd6c - nd6d)))
/4).
DESCRIPTIVES nd6partlikes.
COMPUTE STDnd6partlikes = abs(1- (nd6partlikes/4)).
DESCRIPTIVES STDnd6partlikes.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd6partlikes
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 7: CANDIDATE AFFECT 

Freq candaff_angdpc candaff_hpdpc candaff_afrdpc candaff_prddpc
candaff_angrpc candaff_hprpc candaff_afrrpc candaff_prdrpc.
RECODE candaff_angdpc candaff_hpdpc candaff_afrdpc candaff_prddpc
candaff_angrpc candaff_hprpc candaff_afrrpc candaff_prdrpc (1=1) (2=0) INTO 
candaff_angdpcRC candaff_hpdpcRC candaff_afrdpcRC candaff_prddpcRC
candaff_angrpcRC candaff_hprpcRC candaff_afrrpcRC candaff_prdrpcRC.
Freq candaff_angdpcRC candaff_hpdpcRC candaff_afrdpcRC candaff_prddpcRC
candaff_angrpcRC candaff_hprpcRC candaff_afrrpcRC candaff_prdrpcRC.
Freq candaff_angdpcRC candaff_hpdpcRC candaff_afrdpcRC candaff_prddpcRC
candaff_angrpcRC candaff_hprpcRC candaff_afrrpcRC candaff_prdrpcRC.
COMPUTE nd7a = candaff_angdpcRC.
COMPUTE nd7b = candaff_hpdpcRC.
COMPUTE nd7c = candaff_afrdpcRC.
COMPUTE nd7d =  candaff_prddpcRC.
COMPUTE nd7e =      candaff_angrpcRC.
COMPUTE nd7f =      candaff_hprpcRC.
COMPUTE nd7g =      candaff_afrrpcRC.
COMPUTE nd7h =      candaff_prdrpcRC.
DESCRIPTIVES nd7a nd7b nd7c nd7d nd7e nd7f nd7g nd7h.

COMPUTE nd7candaffect = 
(
(sqrt(abs(nd7a - nd7b))) + 
(sqrt(abs(nd7a - nd7c))) + 
(sqrt(abs(nd7a - nd7d))) + 
(sqrt(abs(nd7a - nd7e))) + 
(sqrt(abs(nd7a - nd7f))) + 
(sqrt(abs(nd7a - nd7g))) + 
(sqrt(abs(nd7a - nd7h))) + 
(sqrt(abs(nd7b - nd7c))) + 
(sqrt(abs(nd7b - nd7d))) + 
(sqrt(abs(nd7b - nd7e))) + 
(sqrt(abs(nd7b - nd7f))) + 
(sqrt(abs(nd7b - nd7g))) + 
(sqrt(abs(nd7b - nd7h))) + 
(sqrt(abs(nd7c - nd7d))) +
(sqrt(abs(nd7c - nd7e))) +
(sqrt(abs(nd7c - nd7f))) +
(sqrt(abs(nd7c - nd7g))) +
(sqrt(abs(nd7c - nd7h))) +
(sqrt(abs(nd7d - nd7e))) +
(sqrt(abs(nd7d - nd7f))) +
(sqrt(abs(nd7d - nd7g))) +
(sqrt(abs(nd7d - nd7h))) +
(sqrt(abs(nd7e - nd7f))) +
(sqrt(abs(nd7e - nd7g))) +
(sqrt(abs(nd7e - nd7h))) +
(sqrt(abs(nd7f - nd7g))) +
(sqrt(abs(nd7f - nd7h))) +
(sqrt(abs(nd7g - nd7h)))
/8).
DESCRIPTIVES nd7candaffect.
COMPUTE STDnd7candaffect = abs(1- (nd7candaffect/16)).
DESCRIPTIVES STDnd7candaffect.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd7candaffect
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 8 IDEOLOGY

Freq libcpre_dpc libcpre_rpc libcpre_ptyd libcpre_ptyr.
MISSING VALUES libcpre_dpc libcpre_rpc libcpre_ptyd libcpre_ptyr (-9, -8).
Freq libcpre_dpc libcpre_rpc libcpre_ptyd libcpre_ptyr.
COMPUTE nd9a = libcpre_dpc.
COMPUTE nd9b = libcpre_rpc.
COMPUTE nd9c = libcpre_ptyd.
COMPUTE nd9d =      libcpre_ptyr.
Freq nd9a nd9b nd9c nd9d.

COMPUTE nd9ideology = 
(
(sqrt(abs(nd9a - nd9b))) + 
(sqrt(abs(nd9a - nd9c))) + 
(sqrt(abs(nd9a - nd9d))) + 
(sqrt(abs(nd9b - nd9c))) + 
(sqrt(abs(nd9b - nd9d))) + 
(sqrt(abs(nd9c - nd9d)))
/4).
DESCRIPTIVES nd9ideology.
COMPUTE STDnd9ideology = abs(1- (nd9ideology/9.58)).
DESCRIPTIVES STDnd9ideology.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd9ideology
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 9 STD EFFICACY

Freq effic_complicstd effic_undstd effic_carestd effic_saystd.
RECODE effic_complicstd effic_undstd effic_carestd effic_saystd
(1=5) (2=4) (3=3) (4=2) (5=1) INTO 
effic_complicstdRC effic_undstdRC effic_carestdRC effic_saystdRC.
VALUE LABELS
effic_complicstdRC effic_undstdRC effic_carestdRC effic_saystdRC
1 'Disagree strongly'
2 'Disagree'
3 'Neither'
4 'Agree'
5 'Agree strongly'.
Freq effic_complicstdRC effic_undstdRC effic_carestdRC effic_saystdRC.
Freq effic_complicstdRC effic_undstdRC effic_carestdRC effic_saystdRC.
COMPUTE nd10a = effic_complicstdRC.
COMPUTE nd10b = effic_undstdRC.
COMPUTE nd10c = effic_carestdRC.
COMPUTE nd10d =      effic_saystdRC.
DESCRIPTIVES nd10a nd10b nd10c nd10d.

COMPUTE nd10stdefficacy = 
(
(sqrt(abs(nd10a - nd10b))) + 
(sqrt(abs(nd10a - nd10c))) + 
(sqrt(abs(nd10a - nd10d))) + 
(sqrt(abs(nd10b - nd10c))) + 
(sqrt(abs(nd10b - nd10d))) + 
(sqrt(abs(nd10c - nd10d)))
/4).
DESCRIPTIVES nd10stdefficacy.
COMPUTE STDnd10stdefficacy = abs(1- (nd10stdefficacy/8.46)).
DESCRIPTIVES STDnd10stdefficacy.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd10stdefficacy
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 10 REV EFFICACY

Freq effic_complicrev effic_undrev effic_carerev effic_sayrev.
RECODE effic_complicrev effic_undrev effic_carerev effic_sayrev 
(1=5) (2=4) (3=3) (4=2) (5=1) INTO 
effic_complicrevRC effic_undrevRC effic_carerevRC effic_sayrevRC.
VALUE LABELS
effic_complicrevRC effic_undrevRC effic_carerevRC effic_sayrevRC
1 'Not at all'
2 'A little'
3 'A moderate amount'
4 'A lot'
5 'A great deal'.
Freq effic_complicrevRC effic_undrevRC effic_carerevRC effic_sayrevRC.
Freq effic_complicrevRC effic_undrevRC effic_carerevRC effic_sayrevRC.
COMPUTE nd11a = effic_complicrevRC.
COMPUTE nd11b = effic_undrevRC.
COMPUTE nd11c = effic_carerevRC.
COMPUTE nd11d =      effic_sayrevRC.
DESCRIPTIVES nd11a nd11b nd11c nd11d.

COMPUTE nd11revefficacy = 
(
(sqrt(abs(nd11a - nd11b))) + 
(sqrt(abs(nd11a - nd11c))) + 
(sqrt(abs(nd11a - nd11d))) + 
(sqrt(abs(nd11b - nd11c))) + 
(sqrt(abs(nd11b - nd11d))) + 
(sqrt(abs(nd11c - nd11d)))
/4).
DESCRIPTIVES nd11revefficacy.
COMPUTE STDnd11revefficacy = abs(1- (nd11revefficacy/8.46)).
DESCRIPTIVES STDnd11revefficacy.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd11revefficacy
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 11 ECON PERCEPTIONS

Freq econ_ecpast_x econ_ecnext_x econ_unpast_x.
RECODE econ_ecpast_x econ_ecnext_x econ_unpast_x
(1=5) (2=4) (3=3) (4=2) (5=1) INTO 
econ_ecpast_xRC econ_ecnext_xRC econ_unpast_xRC.
VALUE LABELS
econ_ecpast_xRC econ_ecnext_xRC econ_unpast_xRC
1 'Much worse'
2 'Somewhat worse'
3 'Same'
4 'Somewhat better'
5 'Much better'.
Freq econ_ecpast_xRC econ_ecnext_xRC econ_unpast_xRC.

Freq econ_ecpast_xRC econ_ecnext_xRC econ_unpast_xRC.
COMPUTE nd12a = econ_ecpast_xRC.
COMPUTE nd12b = econ_ecnext_xRC.
COMPUTE nd12c = econ_unpast_xRC.
DESCRIPTIVES nd12a nd12b nd12c .

COMPUTE nd12econperc = 
(
(sqrt(abs(nd12a - nd12b))) + 
(sqrt(abs(nd12a - nd12c))) + 
(sqrt(abs(nd12b - nd12c))) /3).
DESCRIPTIVES nd12econperc.
COMPUTE STDnd12econperc= abs(1- (nd12econperc/4.07)).
DESCRIPTIVES STDnd12econperc.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd12econperc
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 12: ECON BLAME 

Freq ecblame_pres ecblame_fmpr ecblame_dem ecblame_rep ecblame_bank ecblame_cons ecblame_lend.
RECODE ecblame_pres ecblame_fmpr ecblame_dem ecblame_rep ecblame_bank ecblame_cons ecblame_lend
(1=5) (2=4) (3=3) (4=2) (5=1) INTO 
ecblame_presRC ecblame_fmprRC ecblame_demRC ecblame_repRC ecblame_bankRC ecblame_consRC ecblame_lendRC.
VALUE LABELS
ecblame_presRC ecblame_fmprRC ecblame_demRC ecblame_repRC ecblame_bankRC ecblame_consRC ecblame_lendRC
1 'Not at all'
2 'A little'
3 'A moderate amount'
4 'A lot'
5 'A great deal'.
Freq ecblame_presRC ecblame_fmprRC ecblame_demRC ecblame_repRC ecblame_bankRC ecblame_consRC ecblame_lendRC.

Freq ecblame_presRC ecblame_fmprRC ecblame_demRC ecblame_repRC 
ecblame_bankRC ecblame_consRC ecblame_lendRC.
COMPUTE nd13a = ecblame_presRC.
COMPUTE nd13b = ecblame_fmprRC.
COMPUTE nd13c = ecblame_demRC.
COMPUTE nd13d =  ecblame_repRC.
COMPUTE nd13e =      ecblame_bankRC.
COMPUTE nd13f =      ecblame_consRC.
COMPUTE nd13g =      ecblame_lendRC.
DESCRIPTIVES nd13a nd13b nd13c nd13d nd13e nd13f nd13g.

COMPUTE nd13econblame = 
(
(sqrt(abs(nd13a - nd13b))) + 
(sqrt(abs(nd13a - nd13c))) + 
(sqrt(abs(nd13a - nd13d))) + 
(sqrt(abs(nd13a - nd13e))) + 
(sqrt(abs(nd13a - nd13f))) + 
(sqrt(abs(nd13a - nd13g))) + 
(sqrt(abs(nd13b - nd13c))) + 
(sqrt(abs(nd13b - nd13d))) + 
(sqrt(abs(nd13b - nd13e))) + 
(sqrt(abs(nd13b - nd13f))) + 
(sqrt(abs(nd13b - nd13g))) + 
(sqrt(abs(nd13c - nd13d))) +
(sqrt(abs(nd13c - nd13e))) +
(sqrt(abs(nd13c - nd13f))) +
(sqrt(abs(nd13c - nd13g))) +
(sqrt(abs(nd13d - nd13e))) +
(sqrt(abs(nd13d - nd13f))) +
(sqrt(abs(nd13d - nd13g))) +
(sqrt(abs(nd13e - nd13f))) +
(sqrt(abs(nd13e - nd13g))) +
(sqrt(abs(nd13f - nd13g))) /7).
DESCRIPTIVES nd13econblame.
COMPUTE STDnd13econblame = abs(1- (nd13econblame/27.27)).
DESCRIPTIVES STDnd13econblame.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd13econblame
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 13: CANDIDATE TRAITS 

Freq ctrait_dpcmoral ctrait_dpclead ctrait_dpccare ctrait_dpcknow ctrait_dpcint ctrait_dpchonst.
RECODE ctrait_dpcmoral ctrait_dpclead ctrait_dpccare ctrait_dpcknow ctrait_dpcint ctrait_dpchonst
(1=5) (2=4) (3=3) (4=2) (5=1) INTO 
ctrait_dpcmoralRC ctrait_dpcleadRC ctrait_dpccareRC ctrait_dpcknowRC ctrait_dpcintRC ctrait_dpchonstRC.
VALUE LABELS
ctrait_dpcmoralRC ctrait_dpcleadRC ctrait_dpccareRC ctrait_dpcknowRC ctrait_dpcintRC ctrait_dpchonstRC
1 'Not well at all'
2 'Slightly well'
3 'Moderately well'
4 'Very well'
5 'Extremely well'.
Freq ctrait_dpcmoralRC ctrait_dpcleadRC ctrait_dpccareRC ctrait_dpcknowRC ctrait_dpcintRC ctrait_dpchonstRC.

Freq ctrait_rpcmoral ctrait_rpclead ctrait_rpccare ctrait_rpcknow ctrait_rpcint ctrait_rpchonst.
RECODE ctrait_rpcmoral ctrait_rpclead ctrait_rpccare ctrait_rpcknow ctrait_rpcint ctrait_rpchonst
(1=5) (2=4) (3=3) (4=2) (5=1) INTO 
ctrait_rpcmoralRC ctrait_rpcleadRC ctrait_rpccareRC ctrait_rpcknowRC ctrait_rpcintRC ctrait_rpchonstRC.
VALUE LABELS
ctrait_rpcmoralRC ctrait_rpcleadRC ctrait_rpccareRC ctrait_rpcknowRC ctrait_rpcintRC ctrait_rpchonstRC
1 'Not well at all'
2 'Slightly well'
3 'Moderately well'
4 'Very well'
5 'Extremely well'.
Freq ctrait_rpcmoralRC ctrait_rpcleadRC ctrait_rpccareRC ctrait_rpcknowRC ctrait_rpcintRC ctrait_rpchonstRC.

Freq ctrait_dpcmoralRC ctrait_dpcleadRC ctrait_dpccareRC 
ctrait_dpcknowRC ctrait_dpcintRC ctrait_dpchonstRC.
Freq ctrait_rpcmoralRC ctrait_rpcleadRC ctrait_rpccareRC 
ctrait_rpcknowRC ctrait_rpcintRC ctrait_rpchonstRC.

COMPUTE nd14a = ctrait_dpcmoralRC.
COMPUTE nd14b = ctrait_dpcleadRC.
COMPUTE nd14c = ctrait_dpccareRC.
COMPUTE nd14d =  ctrait_dpcknowRC.
COMPUTE nd14e = ctrait_dpcintRC.
COMPUTE nd14f = ctrait_dpchonstRC.
COMPUTE nd14g = ctrait_rpcmoralRC.
COMPUTE nd14h = ctrait_rpcleadRC.5
COMPUTE nd14i = ctrait_rpccareRC.
COMPUTE nd14j = ctrait_rpcknowRC.
COMPUTE nd14k = ctrait_rpcintRC.
COMPUTE nd14l = ctrait_rpchonstRC.
DESCRIPTIVES nd14a nd14b nd14c nd14d nd14e nd14f 
nd14g nd14h nd14i nd14j nd14k nd14l .

COMPUTE nd14candtrait = 
(
(sqrt(abs(nd14a - nd14b))) + 
(sqrt(abs(nd14a - nd14c))) + 
(sqrt(abs(nd14a - nd14d))) + 
(sqrt(abs(nd14a - nd14e))) + 
(sqrt(abs(nd14a - nd14f))) + 
(sqrt(abs(nd14a - nd14g))) + 
(sqrt(abs(nd14a - nd14h))) + 
(sqrt(abs(nd14a - nd14i))) + 
(sqrt(abs(nd14a - nd14j))) + 
(sqrt(abs(nd14a - nd14k))) + 
(sqrt(abs(nd14a - nd14l))) + 
(sqrt(abs(nd14b - nd14c))) + 
(sqrt(abs(nd14b - nd14d))) + 
(sqrt(abs(nd14b - nd14e))) + 
(sqrt(abs(nd14b - nd14f))) + 
(sqrt(abs(nd14b - nd14g))) + 
(sqrt(abs(nd14b - nd14h))) + 
(sqrt(abs(nd14b - nd14i))) + 
(sqrt(abs(nd14b - nd14j))) + 
(sqrt(abs(nd14b - nd14k))) + 
(sqrt(abs(nd14b - nd14l))) + 
(sqrt(abs(nd14c - nd14d))) +
(sqrt(abs(nd14c - nd14e))) +
(sqrt(abs(nd14c - nd14f))) +
(sqrt(abs(nd14c - nd14g))) +
(sqrt(abs(nd14c - nd14h))) +
(sqrt(abs(nd14c - nd14i))) +
(sqrt(abs(nd14c - nd14j))) +
(sqrt(abs(nd14c - nd14k))) +
(sqrt(abs(nd14c - nd14l))) +
(sqrt(abs(nd14d - nd14e))) +
(sqrt(abs(nd14d - nd14f))) +
(sqrt(abs(nd14d - nd14g))) +
(sqrt(abs(nd14d - nd14h))) +
(sqrt(abs(nd14d - nd14i))) +
(sqrt(abs(nd14d - nd14j))) +
(sqrt(abs(nd14d - nd14k))) +
(sqrt(abs(nd14d - nd14l))) +
(sqrt(abs(nd14e - nd14f))) +
(sqrt(abs(nd14e - nd14g))) +
(sqrt(abs(nd14e - nd14h))) +
(sqrt(abs(nd14e - nd14i))) +
(sqrt(abs(nd14e - nd14j))) +
(sqrt(abs(nd14e - nd14k))) +
(sqrt(abs(nd14e - nd14l))) +
(sqrt(abs(nd14f - nd14g))) +
(sqrt(abs(nd14f - nd14h))) +
(sqrt(abs(nd14f - nd14i))) +
(sqrt(abs(nd14f - nd14j))) +
(sqrt(abs(nd14f - nd14k))) +
(sqrt(abs(nd14f - nd14l))) +
(sqrt(abs(nd14g - nd14h))) +
(sqrt(abs(nd14g - nd14i))) +
(sqrt(abs(nd14g - nd14j))) +
(sqrt(abs(nd14g - nd14k))) +
(sqrt(abs(nd14g - nd14l))) +
(sqrt(abs(nd14h - nd14i))) +
(sqrt(abs(nd14h - nd14j))) +
(sqrt(abs(nd14h - nd14k))) +
(sqrt(abs(nd14h - nd14l))) +
(sqrt(abs(nd14i - nd14j))) +
(sqrt(abs(nd14i - nd14k))) +
(sqrt(abs(nd14i - nd14l))) +
(sqrt(abs(nd14j - nd14k))) +
(sqrt(abs(nd14j - nd14l))) +
(sqrt(abs(nd14k - nd14l)))
/12).
DESCRIPTIVES nd14candtrait.
COMPUTE STDnd14candtrait= abs(1- (nd14candtrait/81.93)).
DESCRIPTIVES STDnd14candtrait.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd14candtrait
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND14: SPENDING AND SERVICES NON-DIFFERENTIATION

Freq spsrvpr_ssself spsrvpr_ssdpc spsrvpr_ssrpc spsrvpr_ssdem spsrvpr_ssrep.
MISSING VALUES spsrvpr_ssself spsrvpr_ssdpc spsrvpr_ssrpc spsrvpr_ssdem spsrvpr_ssrep (-9,-8,-2).

Freq spsrvpr_ssself spsrvpr_ssdpc spsrvpr_ssrpc spsrvpr_ssdem spsrvpr_ssrep.
COMPUTE nd15a = spsrvpr_ssself.
COMPUTE nd15b = spsrvpr_ssdpc.
COMPUTE nd15c = spsrvpr_ssrpc.
COMPUTE nd15d =      spsrvpr_ssdem.
COMPUTE nd15e =      spsrvpr_ssrep.
DESCRIPTIVES nd15a nd15b nd15c nd15d nd15e.

COMPUTE nd15ss = 
(
(sqrt(abs(nd15a - nd15b))) + 
(sqrt(abs(nd15a - nd15c))) + 
(sqrt(abs(nd15a - nd15d))) + 
(sqrt(abs(nd15a - nd15e))) + 
(sqrt(abs(nd15b - nd15c))) + 
(sqrt(abs(nd15b - nd15d))) + 
(sqrt(abs(nd15b - nd15e))) + 
(sqrt(abs(nd15c - nd15d))) +
(sqrt(abs(nd15c - nd15e))) +
(sqrt(abs(nd15d - nd15e)))
/5).
DESCRIPTIVES nd15ss.
COMPUTE STDnd15ss = abs(1- (nd15ss/16.08)).
DESCRIPTIVES STDnd15ss.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd15ss
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND15: DEFENSE SPENDING NON-DIFFERENTIATION

Freq defsppr_self defsppr_dpc defsppr_rpc defsppr_dem defsppr_rep.
MISSING VALUES defsppr_self defsppr_dpc defsppr_rpc defsppr_dem defsppr_rep (-9,-8,-2).

Freq defsppr_self defsppr_dpc defsppr_rpc defsppr_dem defsppr_rep.
COMPUTE nd16a = defsppr_self.
COMPUTE nd16b = defsppr_dpc.
COMPUTE nd16c = defsppr_rpc.
COMPUTE nd16d =      defsppr_dem.
COMPUTE nd16e =      defsppr_rep.
Freq nd16a nd16b nd16c nd16d nd16e.

COMPUTE nd16defspend = 
(
(sqrt(abs(nd16a - nd16b))) + 
(sqrt(abs(nd16a - nd16c))) + 
(sqrt(abs(nd16a - nd16d))) + 
(sqrt(abs(nd16a - nd16e))) + 
(sqrt(abs(nd16b - nd16c))) + 
(sqrt(abs(nd16b - nd16d))) + 
(sqrt(abs(nd16b - nd16e))) + 
(sqrt(abs(nd16c - nd16d))) +
(sqrt(abs(nd16c - nd16e))) +
(sqrt(abs(nd16d - nd16e)))
/5).
DESCRIPTIVES nd16defspend.
COMPUTE STDnd16defspend = abs(1- (nd16defspend/16.27)).
DESCRIPTIVES STDnd16defspend.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd16defspend
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND16: MEDICAL SPENDING NON-DIFFERENTIATION

Freq inspre_self inspre_dpc inspre_rpc inspre_dem inspre_rep.
MISSING VALUES inspre_self inspre_dpc inspre_rpc inspre_dem inspre_rep (-9,-8,-2).

Freq inspre_self inspre_dpc inspre_rpc inspre_dem inspre_rep.
COMPUTE nd17a = inspre_self.
COMPUTE nd17b = inspre_dpc.
COMPUTE nd17c = inspre_rpc.
COMPUTE nd17d =      inspre_dem.
COMPUTE nd17e =      inspre_rep.
Freq nd17a nd17b nd17c nd17d nd17e.

COMPUTE nd17medicalspend = 
(
(sqrt(abs(nd17a - nd17b))) + 
(sqrt(abs(nd17a - nd17c))) + 
(sqrt(abs(nd17a - nd17d))) + 
(sqrt(abs(nd17a - nd17e))) + 
(sqrt(abs(nd17b - nd17c))) + 
(sqrt(abs(nd17b - nd17d))) + 
(sqrt(abs(nd17b - nd17e))) + 
(sqrt(abs(nd17c - nd17d))) +
(sqrt(abs(nd17c - nd17e))) +
(sqrt(abs(nd17d - nd17e)))
/5).
DESCRIPTIVES nd17medicalspend.
COMPUTE STDnd17medicalspend = abs(1- (nd17medicalspend/16.27)).
DESCRIPTIVES STDnd17medicalspend.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd17medicalspend
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND17: GUARJOB

Freq guarpr_self guarpr_dpc guarpr_rpc guarpr_dem guarpr_rep.
MISSING VALUES guarpr_self guarpr_dpc guarpr_rpc guarpr_dem guarpr_rep (-9,-8,-2).


Freq guarpr_self guarpr_dpc guarpr_rpc guarpr_dem guarpr_rep.
COMPUTE nd18a = guarpr_self.
COMPUTE nd18b = guarpr_dpc.
COMPUTE nd18c = guarpr_rpc.
COMPUTE nd18d =      guarpr_dem.
COMPUTE nd18e =      guarpr_rep.
DESCRIPTIVES nd18a nd18b nd18c nd18d nd18e.

COMPUTE nd18guarjob = 
(
(sqrt(abs(nd18a - nd18b))) + 
(sqrt(abs(nd18a - nd18c))) + 
(sqrt(abs(nd18a - nd18d))) + 
(sqrt(abs(nd18a - nd18e))) + 
(sqrt(abs(nd18b - nd18c))) + 
(sqrt(abs(nd18b - nd18d))) + 
(sqrt(abs(nd18b - nd18e))) + 
(sqrt(abs(nd18c - nd18d))) +
(sqrt(abs(nd18c - nd18e))) +
(sqrt(abs(nd18d - nd18e)))
/5).
DESCRIPTIVES nd18guarjob.
COMPUTE STDnd18guarjob= abs(1- (nd18guarjob/16.08)).
DESCRIPTIVES STDnd18guarjob.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd18guarjob
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 18 AID BLACKS

Freq aidblack_self aidblack_dpc aidblack_rpc.
MISSING VALUES aidblack_self aidblack_dpc aidblack_rpc (-9,-8,-2).

Freq aidblack_self aidblack_dpc aidblack_rpc.
COMPUTE nd19a = aidblack_self.
COMPUTE nd19b = aidblack_dpc.
COMPUTE nd19c = aidblack_rpc.
DESCRIPTIVES nd19a nd19b nd19c .

COMPUTE nd19aidblacks = 
(
(sqrt(abs(nd19a - nd19b))) + 
(sqrt(abs(nd19a - nd19c))) + 
(sqrt(abs(nd19b - nd19c))) /3).
DESCRIPTIVES nd19aidblacks.
COMPUTE STDnd19aidblacks= abs(1- (nd19aidblacks/5.02)).
DESCRIPTIVES STDnd19aidblacks.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd19aidblacks
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 19 ENVIRONMENT

Freq envjob_self envjob_dpc envjob_rpc.
MISSING VALUES envjob_self envjob_dpc envjob_rpc (-9,-8,-2).

Freq envjob_self envjob_dpc envjob_rpc.
COMPUTE nd20a = envjob_self.
COMPUTE nd20b = envjob_dpc.
COMPUTE nd20c = envjob_rpc.
DESCRIPTIVES nd20a nd20b nd20c .

COMPUTE nd20environ = 
(
(sqrt(abs(nd20a - nd20b))) + 
(sqrt(abs(nd20a - nd20c))) + 
(sqrt(abs(nd20b - nd20c))) /3).
DESCRIPTIVES nd20environ.
COMPUTE STDnd20environ= abs(1- (nd20environ/5.02)).
DESCRIPTIVES STDnd20environ.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd20environ
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 20: FEDERAL SPENDING

Freq fedspend_ss fedspend_schools fedspend_scitech fedspend_crime
fedspend_welfare fedspend_child fedspend_poor fedspend_enviro.
RECODE fedspend_ss fedspend_schools fedspend_scitech fedspend_crime
fedspend_welfare fedspend_child fedspend_poor fedspend_enviro 
(1=3) (2=1) (3=2) INTO 
fedspend_ssRC fedspend_schoolsRC fedspend_scitechRC fedspend_crimeRC
fedspend_welfareRC fedspend_childRC fedspend_poorRC fedspend_enviroRC.
VALUE LABELS
fedspend_ssRC fedspend_schoolsRC fedspend_scitechRC fedspend_crimeRC
fedspend_welfareRC fedspend_childRC fedspend_poorRC fedspend_enviroRC
1 'Decreased'
2 'Keep same'
3 'Increase'.
Freq fedspend_ssRC fedspend_schoolsRC fedspend_scitechRC fedspend_crimeRC
fedspend_welfareRC fedspend_childRC fedspend_poorRC fedspend_enviroRC.

Freq fedspend_ssRC fedspend_schoolsRC fedspend_scitechRC fedspend_crimeRC
fedspend_welfareRC fedspend_childRC fedspend_poorRC fedspend_enviroRC.

COMPUTE nd21a = fedspend_ssRC.
COMPUTE nd21b = fedspend_schoolsRC.
COMPUTE nd21c = fedspend_scitechRC.
COMPUTE nd21d =      fedspend_crimeRC.
COMPUTE nd21e =      fedspend_welfareRC.
COMPUTE nd21f =      fedspend_childRC.
COMPUTE nd21g =      fedspend_poorRC.
COMPUTE nd21h =      fedspend_enviroRC.
DESCRIPTIVES nd21a nd21b nd21c nd21d nd21e nd21f nd21g nd21h.

COMPUTE nd21fedspending = 
(
(sqrt(abs(nd21a - nd21b))) + 
(sqrt(abs(nd21a - nd21c))) + 
(sqrt(abs(nd21a - nd21d))) + 
(sqrt(abs(nd21a - nd21e))) + 
(sqrt(abs(nd21a - nd21f))) + 
(sqrt(abs(nd21a - nd21g))) + 
(sqrt(abs(nd21a - nd21h))) + 
(sqrt(abs(nd21b - nd21c))) + 
(sqrt(abs(nd21b - nd21d))) + 
(sqrt(abs(nd21b - nd21e))) + 
(sqrt(abs(nd21b - nd21f))) + 
(sqrt(abs(nd21b - nd21g))) + 
(sqrt(abs(nd21b - nd21h))) + 
(sqrt(abs(nd21c - nd21d))) +
(sqrt(abs(nd21c - nd21e))) +
(sqrt(abs(nd21c - nd21f))) +
(sqrt(abs(nd21c - nd21g))) +
(sqrt(abs(nd21c - nd21h))) +
(sqrt(abs(nd21d - nd21e))) +
(sqrt(abs(nd21d - nd21f))) +
(sqrt(abs(nd21d - nd21g))) +
(sqrt(abs(nd21d - nd21h))) +
(sqrt(abs(nd21e - nd21f))) +
(sqrt(abs(nd21e - nd21g))) +
(sqrt(abs(nd21e - nd21h))) +
(sqrt(abs(nd21f - nd21g))) +
(sqrt(abs(nd21f - nd21h))) +
(sqrt(abs(nd21g - nd21h)))
/8).
DESCRIPTIVES nd21fedspending.
COMPUTE STDnd21fedspending = abs(1- (nd21fedspending/24.73)).
DESCRIPTIVES STDnd21fedspending.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd21fedspending
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.

***ND 21: MEDIA USE

Freq medsrc_campsrcs_tvnews medsrc_campsrcs_newsp medsrc_campsrcs_tvtalk 
medsrc_campsrcs_inet medsrc_campsrcs_radio .
COMPUTE nd22a = medsrc_campsrcs_tvnews.
COMPUTE nd22b = medsrc_campsrcs_newsp.
COMPUTE nd22c = medsrc_campsrcs_tvtalk.
COMPUTE nd22d =      medsrc_campsrcs_inet.
COMPUTE nd22e =      medsrc_campsrcs_radio.
DESCRIPTIVES nd22a nd22b nd22c nd22d nd22e.

COMPUTE nd22media = 
(
(sqrt(abs(nd22a - nd22b))) + 
(sqrt(abs(nd22a - nd22c))) + 
(sqrt(abs(nd22a - nd22d))) + 
(sqrt(abs(nd22a - nd22e))) + 
(sqrt(abs(nd22b - nd22c))) + 
(sqrt(abs(nd22b - nd22d))) + 
(sqrt(abs(nd22b - nd22e))) + 
(sqrt(abs(nd22c - nd22d))) +
(sqrt(abs(nd22c - nd22e))) +
(sqrt(abs(nd22d - nd22e)))
/5).
DESCRIPTIVES nd22media.
COMPUTE STDnd22media = abs(1- (nd22media/6)).
DESCRIPTIVES STDnd22media.

REGRESSION
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN
  /DEPENDENT STDnd22media
  /METHOD=ENTER NumberSurveys female agecats married educ working white Internet HHLandline incomePre Indep Rep Mod Cons.


******TABLE 5 & 6 - 

***USE:
* Addicted to Surveys - Table 5 & 6 Models Syntax

*TABLE CREATION

GET DATA
  /TYPE=XLSX
  /FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/ANES 2012/Addicted to Surveys - Table 5 and 6 Variables for Analysis.xlsx'
  /SHEET=name 'Variables for Analysis'
  /CELLRANGE=FULL
  /READNAMES=ON
  /DATATYPEMIN PERCENTAGE=95.0
  /HIDDEN IGNORE=YES.
EXECUTE.
DATASET NAME DataSet1 WINDOW=FRONT.

RENAME VARIABLES (VariableName = VN).
EXECUTE.

SELECT IF (VN NE "").
EXE.

DESCRIPTIVES NumberSig TimeSig RateSig.
Freq NumberSig.

RECODE NumberSig TimeSig RateSig NumSurveysDummySig (0 THRU 0.1 = 1) (0.10001 THRU HI =0) 
INTO NumberSig1 TimeSig1 RateSig1 NumSurveysDummySig1.
Freq NumberSig1 TimeSig1 RateSig1 NumSurveysDummySig.

RECODE NumberSig TimeSig RateSig NumSurveysDummySig (0 THRU 0.05 = 1) (0.05001 THRU HI =0) 
INTO NumberSig05 TimeSig05 RateSig05 NumSurveysDummySig05.
Freq NumberSig05 TimeSig05 RateSig05 NumSurveysDummySig05.

IF (VariableLabel= 'PRE: Affect for Democratic Pres cand: angry') GeneralType = 'Dichotomous'.
Freq GeneralType.


****ANALYSIS FOR PAPER

*TABLE 5 - BASIC BREAKDOWN

TEMP.
SELECT IF (GeneralType = 'Likert').
Freq  NumSurveysDummySig05.


**TABLE 6

Freq QuestionType.
STRING QuestionTypeCondensed (A9).
COMPUTE QuestionTypeCondensed = QuestionType.
RECODE QuestionTypeCondensed ('Therm'='Attitude').
Freq QuestionTypeCondensed.

TEMP.
SELECT IF (GeneralType NE 'Dichotomous').
CROSS NumSurveysDummySig05 BY QuestionTypeCondensed
    /cells = col count.



*************************************INDIRECT TESTS OF RELATIONSHIPS

GET
  FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 Analysis/anes_timeseries_cdf.sav'.
DATASET NAME DataSet1 WINDOW=FRONT.

Freq VCF0004.
SELECT IF (VCF0004=2012 OR VCF0004=2016).
Freq VCF0004.
IF (VCF0004=2012) ProfessionalRespondents=1.
IF (VCF0004=2016) ProfessionalRespondents=0.
Freq ProfessionalRespondents.

Freq VCF0017.
RECODE VCF0017 (0=0) (4=1) INTO WebMode.
VALUE LABELS 
WebMode
0 'FTF'
1 'Web'.
Freq WebMode.

CROSS WebMode BY ProfessionalRespondents.
IF (WebMode =1 AND ProfessionalRespondents=1) ModeYear=1.
IF (WebMode =1 AND ProfessionalRespondents=0) ModeYear=2.
IF (WebMode =0 AND ProfessionalRespondents=1) ModeYear=3.
IF (WebMode =0 AND ProfessionalRespondents=0) ModeYear=4.
VALUE LABELS 
ModeYear 
1 'Web - 2012'
2 'Web - 2016'
3 'FTF - 2012'
4 'FTF - 2016'.
Freq ModeYear.

Freq VCF0104.
RECODE VCF0104 (0=-9) (1=0) (2=1) (3=0) INTO Female. 
MISSING VALUES Female (-9).
VALUE LABELS 
Female
0 'Male'
1 'Female'.
Freq Female.

Freq VCF0101.
COMPUTE Age = VCF0101.
MISSING VALUES Age (0).
Freq Age. 
RECODE Age (18 THRU 30=1) (31 THRU 45=2) (46 THRU 60=3) (61 THRU HI =4) INTO AgeCats.
VALUE LABELS
AgeCats
1 '18-30'
2 '31-45'
3 '46-60'
4 '61+'.
Freq AgeCats.
RECODE AgeCats (1=1) (2=0) (3 THRU 4 =0) INTO Age18.
RECODE AgeCats (1=0) (2=1) (3 THRU 4 =0) INTO Age31.
RECODE AgeCats (1 THRU 2 =0) (3=1) (4 =0) INTO Age46.
RECODE AgeCats (1 THRU 3 =0) (4 =1) INTO Age61.
Freq Age18 Age31 Age46 Age61.

Freq VCF0147.
RECODE VCF0147 (1=1) (2 THRU 7=0) (9=-9) INTO Married.
MISSING VALUES Married (-9).
VALUE LABELS 
Married 
0 'Not Married'
1 'Married'.
Freq Married. 

Freq VCF0140 VCF0140a.
RECODE VCF0140a (1 THRU 2=1) (3 THRU 4=2) (5=3) (6=4)(7=5) INTO Educ.
VALUE LABELS 
Educ
1 'Less than HS'
2 'HS Credential'
3 'Some post-HS'
4 'Bachelor’s Degree'
5 'Graduate Degree'.
Freq Educ. 
RECODE Educ (1=1) (2=0) (3 THRU 5 =0) INTO EducLTHS.
RECODE Educ (1=0) (2=1) (3 THRU 5 =0) INTO EducHS.
RECODE Educ (1 THRU 2 =0) (3=1) (4 THRU 5 =0) INTO EducSomeC.
RECODE Educ (1 THRU 3 =0) (4 =1) (5=0) INTO EducBA.
RECODE Educ (1 THRU 4 =0) (5 =1) INTO EducGrad.
Freq EducLTHS EducHS EducSomeC EducBA EducGrad.

Freq VCF0116.
RECODE VCF0116 (1=1) (2 THRU 8=0) INTO Working.
VALUE LABELS
Working
0 'Not Working'
1 'Working'.
Freq Working. 

Freq VCF0105a.
RECODE VCF0105a (1=1) (2 THRU 6=0) INTO White.
VALUE LABELS 
White 
0 'Non-White'
1 'White'.
Freq White. 
RECODE VCF0105a (1=0) (2=1) (3 THRU 6=0) INTO Black.
VALUE LABELS 
Black 
0 'Non-Black'
1 'Black'.
Freq Black. 
RECODE VCF0105a (1 THRU 4=0) (5=1) ( 6=0) INTO Hispanic.
VALUE LABELS 
Hispanic 
0 'Non-Hispanic'
1 'Hispanic'.
Freq Hispanic. 
RECODE VCF0105a (1 THRU 2=0) (3=1)  (4 THRU 6=0) INTO Asian.
VALUE LABELS 
Asian 
0 'Non-Asian'
1 'Asian'.
Freq Asian. 


Freq VCF0301.
COMPUTE PartyID7 = VCF0301.
MISSING VALUES PartyID7 (0).
VALUE LABELS
PartyID7
1 'Strong Democrat'
2 'Weak Democrat'
3 'Independent - Democrat'
4 'Independent'
5 'Independent - Republican'
6 'Weak Republican'
7 'Strong Republican'.
Freq PartyID7.

RECODE PartyID7 (1 THRU 3 =1) (4 THRU 7=0) INTO Democrat.
RECODE PartyID7 (1 THRU 3 =0) (4=1) (5 THRU 7=0) INTO Independent.
RECODE PartyID7 (1 THRU 4 =0) (5 THRU 7=1) INTO Republican.
Freq Democrat Independent Republican.

Freq VCF0803.
COMPUTE Ideology = VCF0803. 
MISSING VALUES Ideology (0,9). 
VALUE LABELS
Ideology
1 'Extremely Liberal'
2 'Liberal'
3 'Slightly Liberal'
4 'Moderate'
5 'Slightly Conservative'
6 'Conservative'
7 'Extremely Conservative'.
Freq Ideology. 

RECODE Ideology (1 THRU 3 =1) (4 THRU 7=0) INTO Liberal.
RECODE Ideology (1 THRU 3 =0) (4=1) (5 THRU 7=0) INTO Moderate.
RECODE Ideology (1 THRU 4 =0) (5 THRU 7=1) INTO Conservative.
RECODE VCF0803 (1 THRU 7=0) (9=1) INTO NoThoughtIdeology.
Freq Liberal Moderate Conservative NoThoughtIdeology.

Freq VCF0310.
COMPUTE Interest= VCF0310.
VALUE LABELS 
Interest
1 'Not much interested'
2 'Somewhat interested'
3 'Very much interested'.
MISSING VALUES Interest (0).
Freq Interest.
RECODE Interest (1=1) (2 THRU 3 =0) INTO IntNotMuch.
RECODE Interest (1=0) (2=1) (3=0) INTO IntSomewhat.
RECODE Interest (1 THRU 2=0) (3=1) INTO IntVery.
Freq IntNotMuch IntSomewhat IntVery.


**MERGING IN  YEAR SPECIFIC INFO 

****2012 

GET
  FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 Analysis/anes_timeseries_2012.sav'.
ALTER TYPE ALL(A=AMIN).
DATASET NAME DataSet2 WINDOW=FRONT.


DESCRIPTIVES caseid.
EXE.
STRING Zero (A1).
STRING Zero2 (A2).
STRING Zero3 (A3).
COMPUTE Zero = '0'.
COMPUTE Zero2='00'.
COMPUTE Zero3 = '000'.
EXE.

COMPUTE caseidb = caseid.
ALTER TYPE caseidb (F4).
ALTER TYPE caseidb (A4).
EXECUTE.

STRING caseid1 caseid2 caseid3(A4).
COMPUTE caseid3 = concat(Zero3, LTRIM(caseidb)).
COMPUTE caseid2 = concat(Zero2, LTRIM(caseidb)).
COMPUTE caseid1 = concat(Zero, LTRIM(caseidb)).
EXE.

STRING CaseidFinal (A4).
IF (caseid  LT 10) CaseidFinal = caseid3.
IF (caseid  GT 9 AND caseid LT 100) CaseidFinal = caseid2.
IF (caseid  GT 99 AND caseid LT 1000) CaseidFinal = caseid1.
IF (caseid GT 999) CaseidFinal = caseidb.
EXE.

STRING VCF0006a (A8).
EXE.
STRING Year (A4).
EXECUTE.
COMPUTE Year = "2012".
EXE.
COMPUTE VCF0006a = concat(Year,CaseidFinal).
EXE.
ALTER TYPE VCF0006a (F8).
EXE.

DELETE VARIABLES Zero Zero2 Zero3 caseidb caseid1
caseid2 caseid3 CaseidFinal.
EXE.

*KEEP 
VCF0006a inc_incgroup_pre admin_pre_iwlength dem2_inethome dem2_landline dem2_cellnum profile_surveyscompleted
wordsum_setb wordsum_setd wordsum_sete wordsum_setf
wordsum_setg wordsum_seth wordsum_setj wordsum_setk
wordsum_setl wordsum_seto 

SAVE OUTFILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 '+
    'Analysis/anes_timeseries_2012_truncated for merge.sav'
  /DROP=version caseid weight_ftf weight_web weight_full psu_full psu_ftf strata_full strata_ftf    ftf_oversample wave_completions mode gend_gendobs gender_respondent_x interest_attention    
    interest_following interest_wherevote interest_voted2008 interest_whovote2008    interest_whovote2008_oth prmedia_useinet prmedia_wkinews prmedia_atinews prmedia_wktvnws
    prmedia_attvnews prmedia_wkpaprnws prmedia_atpprnews prmedia_wkrdnws prmedia_atrdnews    prevote_regist_addr prevote_regist_noaddr prevote_reg prevote_reg_recordstate 
   prevote_reg_recordcity prevote_reg_state prevote_reg_samestate prevote_regincnty prevote_regyrs3cat    prevote_regyrsfull prevote_regname prevote_regpty_state prevote_regpty prevote_regpty_oth
    prevote_regint prevote_primv prevote_primvwho prevote_primvwho_oth prevote_voted prevote_vconf    prevote_howvote prevote_ckbcard prevote_ballot_color prevote_presvt prevote_presvtwho
    prevote_presvtwho_oth prevote_presstr prevote_vtpresdec prevote_vtpresdec_dkrf prevote_intpres    prevote_intpreswho prevote_intpreswho_oth prevote_intpresst prevote_prefpres prevote_prefprwho
    prevote_prefprwho_oth prevote_prefprstr prevote_votehs prevote_hsvtbc prevote_hsvtnobc    prevote_inths prevote_inthsbc prevote_inthsnobc prevote_hspref prevote_hsprefbc prevote_hsprefnobc
    prevote_senhhstate prevote_senregstate prevote_votesen prevote_vtsenbc prevote_vtsennobc    prevote_intsen prevote_intsenbc prevote_intsennobc prevote_senpref prevote_senprefbc
    prevote_senprefnobc prevote_govhhstate prevote_govregstate prevote_votegov prevote_vtgovbc    prevote_vtgovnobc prevote_intgov prevote_intgovbc prevote_intgovnobc prevote_govpref
    prevote_govprefbc prevote_govprefnobc candlik_likedpc candlik_likewhatdpc candlik_disldpc    candlik_dislwhatdpc candlik_likerpc candlik_likewhatrpc candlik_dislrpc candlik_dislwhatrpc
    congapp_job congapp_jobst congapp_job_x presapp_track presapp_job presapp_jobstr presapp_job_x    presapp_econ presapp_econstr presapp_econ_x presapp_foreign presapp_foreignstr presapp_foreign_x
    presapp_health presapp_healthstr presapp_health_x presapp_war presapp_warstr presapp_war_x ft_dpc    ft_rpc ft_dvpc ft_rvpc ft_hclinton ft_gwb ft_dem ft_rep ptylik_likdp ptylik_lwhatdp ptylik_disldp
    ptylik_dwhatdp ptylik_likrp ptylik_lwhatrp ptylik_dislrp ptylik_dwhatrp finance_finfam    finance_finpast finance_finpastamt finance_finpast_x finance_finnext finance_finnextamt
    finance_finnext_x health_insured health_2010hcr health_2010hcrfav health_2010hcropp    health_2010hcr_x health_self health_smoke health_smokeamt candaff_angdpc candaff_angdpcoft
    candaff_hpdpc candaff_hpdpcoft candaff_afrdpc candaff_afrdpcoft candaff_prddpc candaff_prddpcoft    candaff_angrpc candaff_angrpcoft candaff_hprpc candaff_hprpcoft candaff_afrrpc candaff_afrrpcoft
    candaff_prdrpc candaff_prdrpcoft libcpre_self libcpre_choose libcpre_dpc libcpre_rpc libcpre_ptyd    libcpre_ptyr divgov_splitgov likelypct_howlikvt1 likelypct_whatpct1 campfin_limcorp campfin_banads
    ineq_incgap ineq_gapmore ineq_gapless ineq_incgap_x effic_complicstd effic_undstd effic_carestd    effic_saystd effic_complicrev effic_undrev effic_carerev effic_sayrev econ_ecnow econ_ecpast
    econ_ecpastamt econ_ecpast_x econ_ecnext econ_ecnextamt econ_ecnext_x econ_unpast econ_unlast    econ_unpast_x econ_unnext ecblame_pres ecblame_fmpr ecblame_dem ecblame_rep ecblame_bank
    ecblame_cons ecblame_lend ptyperf_ptyecon preswin_care preswin_win preswin_win_oth preswin_close    preswin_state preswin_state_oth preswin_closest preswin_dutychoice preswin_choiceduty
    preswin_dutyst preswin_choicest preswin_dutychoice_x usworld_stronger usworld_stay pid_self    pid_self_oth pid_strong pid_lean pid_x tea_supp tea_suppstr tea_suppln tea_supp_x ctrait_dpcmoral
    ctrait_dpclead ctrait_dpccare ctrait_dpcknow ctrait_dpcint ctrait_dpchonst ctrait_rpcmoral    ctrait_rpclead ctrait_rpccare ctrait_rpcknow ctrait_rpcint ctrait_rpchonst war_worthit war_terror
    spsrvpr_ssself spsrvpr_ssdpc spsrvpr_ssrpc spsrvpr_ssdem spsrvpr_ssrep defsppr_self defsppr_dpc    defsppr_rpc defsppr_dem defsppr_rep inspre_self inspre_dpc inspre_rpc inspre_dem inspre_rep
    gun_control gun_importance guarpr_self guarpr_dpc guarpr_rpc guarpr_dem guarpr_rep immig_policy    immig_citizen immig_checks aidblack_self aidblack_dpc aidblack_rpc envjob_self envjob_dpc
    envjob_rpc aa_uni aa_unifav aa_uniopp aa_uni_x aa_work aa_workfav aa_workopp aa_work_x fedspend_ss    fedspend_schools fedspend_scitech fedspend_crime fedspend_welfare fedspend_child fedspend_poor
    fedspend_enviro candrel_dpc candrel_dpc_oth candrel_rpc candrel_rpc_oth trustgov_trustgrev    trustgov_trustgstd trustgov_bigintrst trustgov_waste trustgov_corrpt trust_social respons_elections
    econcand_dwin econcand_rwin envir_drill envir_nuke envir_gwarm envir_gwgood envir_gwhow    gayrt_discrev gayrt_discstrev gayrt_discrev_x gayrt_discstd gayrt_discststd gayrt_discstd_x
    gayrt_milrev gayrt_milstrev gayrt_milrev_x gayrt_milstd gayrt_milststd gayrt_milstd_x gayrt_adopt    gayrt_marry abortpre_4point abortpre_4point_oth penalty_favdpen penalty_dpenstr penalty_favopp_x
    presadm_secure pctlikely_whatpct2 pctlikely_howlikvt2 relig_import relig_guide relig_pray    relig_pray_oth relig_wordgod relig_wordgod_oth relig_church relig_churchoft relig_churchwk
    relig_chmember relig_7cat_x relig_mastersummary relig_group relig_groupna relig_denom relig_bapt    relig_indbapt relig_luth relig_meth relig_presb relig_refrm relig_brethr relig_discp relig_chchrst
    relig_chgod relig_pent relig_denother relig_othxian relig_jewisha relig_jewishna relig_bornagn    relig_ident_1st relig_ident_2nd relig_ident_3rd relig_religident_prog relig_religident_nontrad
    relig_religident_secular relig_religident_agnostic relig_religident_atheist    relig_religident_spiritual relig_religident_none relig_religident_dkrf dem_birthmo dem_birthdy
    dem_birthyr dem_age_r_x dem_agegrp_iwdate_x dem_marital dem_partner dem_edu dem_edu_oth dem_dipged    dem_edugroup_x dem_edusp dem_edusp_oth dem_dipgedsp dem_eduspgroup_x dem_veteran dem_milwhen_1st
    dem_milwhen_2nd dem_milwhen_3rd dem_milwhen_4th dem_milnow dem_emptype_1st dem_emptype_2nd    dem_emptype_3rd dem_emptype_4th dem_emptype_work dem_emptype_layoff dem_emptype_unemp
    dem_emptype_retire dem_emptype_disabled dem_emptype_hmaker dem_emptype_student dem_emptype_dkrf    dem_empstatus_2digitfin_x dem_empstatus_1digitfin_x dem_empstatus_initial dem_hsworkg dem_hsjob6mo
    dem_retiremo dem_retiredy dem_retireyr dem_retireperiod_x dem_everwk dem_occpast dem_indpast    dem_semplpst dem_empgovpst dem_rdjob6mon dem_hrsrecent dem_rdworkg dem_lookwk dem_findjob
    dem_occnow dem_indnow dem_semplnow dem_empgovnow dem_hrsnow dem_okhrsnow dem_losejob dem_offwork    dem_hrsreduce dem_emptypesp_1st dem_emptypesp_2nd dem_emptypesp_3rd dem_emptypesp_4th
    dem_emptypesp_work dem_emptypesp_layoff dem_emptypesp_unemp dem_emptypesp_retire    dem_emptypesp_disabled dem_emptypesp_hmaker dem_emptypesp_student dem_emptypesp_dkrf dem_csesjobsp
    dem_unionhh dem_unionwho_1st dem_unionwho_2nd dem_unionwho_r dem_unionwho_spouse    dem_unionwho_personoth dem_unionwho_dkrf dem_class dem_whichclass dem_whichclass_oth dem_chclass
    dem_chclass_oth dem_avgclass dem_avgclass_oth dem_hisp dem_hisptyp_1st dem_hisptyp_2nd    dem_hisptyp_mex dem_hisptyp_mexam dem_hisptyp_chicano dem_hisptyp_puertorican dem_hisptyp_cuban
    dem_hisptyp_cubanam dem_hisptyp_othhisp dem_hisptyp_dkrf dem_hispoth dem_hispmost dem_hispmost_oth    dem_racecps_1st dem_racecps_2nd dem_racecps_3rd dem_racecps_white dem_racecps_black
    dem_racecps_native dem_racecps_asian dem_racecps_pacif dem_racecps_othrace dem_racecps_racedkrf    dem_racecps_oth dem_raceeth_x dem_ethnic dem_numeth dem_mosteth dem_parents dem_nativity
    dem_nativity_oth dem_hispgpar dem_hispcntry dem_hispcntry_oth dem_arr dem_arrperiod dem_cit    dem_citperiod dem_hisplang dem2_ch10less dem2_ch11to17 dem2_numchild dem2_schenrl_1st
    dem2_schenrl_2nd dem2_schenrl_3rd dem2_schenrl_public dem2_schenrl_privrel dem2_schenrl_privnonrel    dem2_schenrl_home dem2_schenrl_enrollno dem2_schenrl_enrolldkrf  dem2_inettyp
    dem2_cellpers dem2_smartph dem3_grewup dem3_yearscomm    dem3_yearscomm_full dem3_moscomm dem3_prevzip dem3_prevcty dem3_ownhome dem3_ownhome_oth
    dem3_namech dem3_namechyr dem3_altname dem3_lenaddr dem3_lenaddr_full dem3_add5yr_state    dem3_add5yr_samestate dem3_driver dem3_passport dem3_govtid casistart_iwrset4 casistart_iwrset6
    selfgend_gender wealth_stocks wealth_whoinvest wealth_vachome wealth_ownrental wealth_stockgrnts    wealth_undland wealth_investbus inc_totinc inc_totmiss40 inc_totmiss20 inc_totl20 inc_totg20l40
    inc_totmiss70 inc_totg40l70 inc_totmiss100 inc_totg70l100 inc_totg100     medsrc_campsrcs_1st medsrc_campsrcs_2nd medsrc_campsrcs_3rd medsrc_campsrcs_4th medsrc_campsrcs_5th
    medsrc_campsrcs_tvnews medsrc_campsrcs_newsp medsrc_campsrcs_tvtalk medsrc_campsrcs_inet    medsrc_campsrcs_radio medsrc_campsrcs_none medsrc_campsrcs_dkrf medsrc_tvprog_01 medsrc_tvprog_02
    medsrc_tvprog_03 medsrc_tvprog_04 medsrc_tvprog_05 medsrc_tvprog_06 medsrc_tvprog_07    medsrc_tvprog_08 medsrc_tvprog_09 medsrc_tvprog_10 medsrc_tvprog_11 medsrc_tvprog_12
    medsrc_tvprog_13 medsrc_tvprog_14 medsrc_tvprog_15 medsrc_tvprog_16 medsrc_tvprog_17    medsrc_tvprog_18 medsrc_tvprog_19 medsrc_tvprog_20 medsrc_tvprog_21 medsrc_tvprog_22
    medsrc_tvprog_23 medsrc_tvprog_24 medsrc_tvprog_25 medsrc_tvprog_26 medsrc_tvprog_27    medsrc_tvprog_28 medsrc_tvprog_29 medsrc_tvprog_30 medsrc_tvprog_31 medsrc_tvprog_32
    medsrc_tvprog_33 medsrc_tvprog_34 medsrc_tvprog_35 medsrc_tvprog_36 medsrc_tvprog_37    medsrc_tvprog_38 medsrc_tvprog_39 medsrc_tvprog_40 medsrc_tvprog_41 medsrc_tvprog_42
    medsrc_tvprog_43 medsrc_tvprog_44 medsrc_tvprog_45 medsrc_tvprog_46 medsrc_tvprog_47    medsrc_tvprog_48 medsrc_tvprog_49 medsrc_tvprog_50 medsrc_tvprog_51 medsrc_tvprog_52
    medsrc_tvprog_53 medsrc_tvprog_54 medsrc_tvprog_55 medsrc_tvprog_56 medsrc_tvprog_57    medsrc_tvprog_58 medsrc_tvprog_59 medsrc_tvprog_60 medsrc_tvprog_61 medsrc_tvprog_62
    medsrc_tvprog_63 medsrc_tvprog_64 medsrc_tvprog_nonescr1 medsrc_tvprog_nonescr2    medsrc_tvprog_nonescr3 medsrc_tvprog_nonescr4 medsrc_tvprog_dkscr1 medsrc_tvprog_dkscr2
    medsrc_tvprog_dkscr3 medsrc_tvprog_dkscr4 medsrc_tvprog_rfscr1 medsrc_tvprog_rfscr2    medsrc_tvprog_rfscr3 medsrc_tvprog_rfscr4 medsrc_radio_01 medsrc_radio_02 medsrc_radio_03
    medsrc_radio_04 medsrc_radio_05 medsrc_radio_06 medsrc_radio_07 medsrc_radio_08 medsrc_radio_09    medsrc_radio_10 medsrc_radio_11 medsrc_radio_12 medsrc_radio_13 medsrc_radio_14 medsrc_radio_15
    medsrc_radio_none medsrc_radio_dkrf medsrc_websites_01 medsrc_websites_02 medsrc_websites_03    medsrc_websites_04 medsrc_websites_05 medsrc_websites_06 medsrc_websites_07 medsrc_websites_08
    medsrc_websites_09 medsrc_websites_10 medsrc_websites_11 medsrc_websites_12 medsrc_websites_13    medsrc_websites_14 medsrc_websites_15 medsrc_websites_othweb medsrc_websites_oth
    medsrc_websites_none medsrc_websites_dkrf medsrc_printnews_01 medsrc_printnews_02    medsrc_printnews_03 medsrc_printnews_04 medsrc_printnews_05 medsrc_printnews_06 medsrc_printnews_07
    medsrc_printnews_08 medsrc_printnews_09 medsrc_printnews_10 medsrc_printnews_11 medsrc_printnews_12    medsrc_printnews_13 medsrc_printnews_14 medsrc_printnews_15 medsrc_printnews_othnews
    medsrc_printnews_none medsrc_printnews_dkrf medsrc_inetnews_01 medsrc_inetnews_02    medsrc_inetnews_03 medsrc_inetnews_04 medsrc_inetnews_05 medsrc_inetnews_06 medsrc_inetnews_07
    medsrc_inetnews_08 medsrc_inetnews_09 medsrc_inetnews_10 medsrc_inetnews_11 medsrc_inetnews_12    medsrc_inetnews_13 medsrc_inetnews_14 medsrc_inetnews_15 medsrc_inetnews_othnews
    medsrc_inetnews_none medsrc_inetnews_dkrf medsrc_socmedia medsrc_blogs medsrc_specblogs    owngun_owngun orientn_rgay orientn_knowgay preknow_prestimes
    preknow_sizedef preknow_senterm preknow_medicare preknow_leastsp happ_lifesatisf mediapo_tv    mediapo_tvamt mediapo_radio mediapo_radioamt mediapo_nwsprev mediapo_nwsprevamt mediapo_net
    mediapo_netamt mediapo_site mediapo_siteamt mobilpo_party mobilpo_wparty mobilpo_wparty_oth    mobilpo_contactoth mobilpo_latino mobilpo_lang mobilpo_reg mobilpo_rmob mobilpo_rally mobilpo_sign
    mobilpo_otherwork mobilpo_ctbcand mobilpo_ctbcndpty mobilpo_ctbcndpty_oth mobilpo_ctbpty    mobilpo_ctbwhpty mobilpo_ctbwhpty_oth mobilpo_ctboth dhsinvolv_march dhsinvolv_board
    dhsinvolv_netpetition dhsinvolv_petition dhsinvolv_relig dhsinvolv_org dhsinvolv_call    dhsinvolv_message dhsinvolv_letter dhsinvolv_contact1 dhsinvolv_contact2_1st dhsinvolv_contact2_2nd
    dhsinvolv_contact2_3rd dhsinvolv_contact2_4th dhsinvolv_contact2_stsen dhsinvolv_contact2_othsen    dhsinvolv_contact2_distrep dhsinvolv_contact2_othrep dhsinvolv_contact2_dkrf postvote_regpre
    postvote_votedpre postvote_prestatus_nonvtr postvote_regist_addr postvote_regist_noaddr    postvote_reg postvote_reg_state postvote_reg_samestate postvote_regincnty postvote_regyrs3cat
    postvote_regyrsfull postvote_regname postvote_regpty_state postvote_regpty postvote_regpty_oth    postvote_rvote rvote2012_x postvote_ckbcard postvote_ballotcolor postvote_presvt postvote_presvtwho
    presvote2012_x postvote_presvtwho_oth postvote_presstr postvote_vtpresdec postvote_vtpresdec_dkrf    postvote_prefpres postvote_prefprwho postvote_prefprwho_oth postvote_prefprstr postvote_votehs
    postvote_hsvtbc postvote_hsvtnobc hsevote2012_x postvote_hspref postvote_hsprefbc    postvote_hsprefnobc postvote_senhhstate postvote_senregstate postvote_votesen postvote_vtsenbc
    postvote_vtsennobc senvote2012_x postvote_senpref postvote_senprefbc postvote_senprefnobc    postvote_govhhstate postvote_govregstate postvote_votegov postvote_vtgovbc postvote_vtgovnobc
    govvote2012_x postvote_govpref postvote_govprefbc postvote_govprefnobc ptywom_bettrpty    ofcrec_speaker ofcrec_speaker_correct ofcrec_speaker_probe ofcrec_vp ofcrec_vp_correct
    ofcrec_vp_probe ofcrec_pmuk ofcrec_pmuk_correct ofcrec_pmuk_probe ofcrec_cj ofcrec_cj_correct    ofcrec_cj_probe ftpo_pres ftpo_rpc ftpo_rpcsp ftpo_dpcsp ftpo_hdc ftpo_hrc ftpo_hoth ftpo_sdc
    ftpo_src ftpo_soth ftpo_sensr ftpo_senjr ftpo_sennot ftpo_dvpc ftpo_rvpc ftpo_roberts ftgr_xfund    ftgr_catholics ftgr_feminists ftgr_fedgov ftgr_liberals ftgr_middle ftgr_unions ftgr_poor
    ftgr_military ftgr_bigbus ftgr_welfare ftgr_cons ftgr_working ftgr_ussc ftgr_gay ftgr_congress    ftgr_rich ftgr_muslims ftgr_xian ftgr_atheists ftgr_mormons ftgr_tea hseinc_approval hseinc_appstr
    hseinc_disstr hseinc_approval_x hseinc_hinctouch mip_problem1 mip_prob1_dkrf mip_prob1pty    mip_problem2 mip_prob2_dkrf mip_prob2pty mip_problem3 mip_prob3_dkrf mip_prob3pty mip_mostproblem
    mip_mostprob_dkrf securpub_secchg knowl_housemaj knowl_senmaj wpres_gdbd wpres_gdstr wpres_bdstr    wpres_gdbd_x wpres_importyes wpres_importno budget_deficit budget_deficitfav budget_deficitopp
    budget_deficitlean budget_deficit_x budget_defimp budget_rdef250k budget_rdefmed budget_rdefctax    budget_rdefmil budget_rdefemp budget_rdefgov patriot_flag patriot_love patriot_amident
    milln_milltax milln_milltaxst milln_milltax_x fairjob_opin fairjob_opin_oth fairjob_yes fairjob_no    fairjob_opin_x imports_limit israel_support immigpo_level immigpo_jobs hlthlaw_qual hlthlaw_num
    iran_nukdev iran_nukdip iran_nuksanct iran_nuksite iran_nukeinvd china_econ china_mil    ecperil_putoffmed ecperil_payhlthcst ecperil_worry ecperil_home ecperil_payany ecperil_payhouse
    ecperil_lostjobs libcpo_self libcpo_selfch libcpo_hdc libcpo_hrc science_use abort_dpc4    abort_dpc4_oth abort_rpc4 abort_rpc4_oth abort_dem4 abort_dem4_oth abort_rep4 abort_rep4_oth
    abort_health abort_healthfav abort_healthopp abort_healthln abort_health_x abort_fatal    abort_fatalfav abort_fatalopp abort_fatalln abort_fatal_x abort_incest abort_incestfav
    abort_incestopp abort_incestln abort_incest_x abort_rape abort_rapefav abort_rapeopp abort_rapelean    abort_rape_x abort_bd abort_bdfav abort_bdopp abort_bdln abort_bd_x abort_fin abort_finfav
    abort_finopp abort_finln abort_fin_x abort_sex abort_sexfav abort_sexopp abort_sexln abort_sex_x    abort_choice abort_choicefav abort_choiceopp abort_choiceln abort_choice_x wiretap_warrant
    outsource_enc outsource_encst outsource_enc_x ssinv_invest ssinv_invfav ssinv_invopp ssinv_invln    ssinv_invest_x neonull_strule neonull_strulest neonull_strule_x pot_legal govrole_big
    govrole_market govrole_lessmore govrole_regbus discuss_disc discuss_discpstwk mormon_xn    mormon_known mormon_beliefs factor_rpcrel factor_dpcrace factor_ahcare factor_econ factor_fpol
    factor_dpcrel factor_rpcwlth factor_pcdem factor_pcrep ptydiff_diff ptycons_cons ptycons_ptyconswh    tarp_favopp tarp_favoppst tarp_favopp_x scourt_elim scourt_elimstr scourt_elimln scourt_elim_x
    scourt_remove scourt_removestr scourt_removeln scourt_remove_x involv_communwk involv_govoffic    involv_commmtg involv_numorgs involv_voltr involv_charity link_black link_blackamt link_hisp
    link_hispamt link_white link_whiteamt link_wom link_womamt link_oth link_othamt trad_adjust    trad_lifestyle trad_tolerant trad_famval resent_workway resent_slavery resent_deserve resent_try
    trustgvpo_crook efficpo_complicstd efficpo_undstd efficpo_carestd efficpo_saystd efficpo_complicrev    efficpo_undrev efficpo_carerev efficpo_sayrev efficpo_bothside electintpo_countfair
    electintpo_jrnlfair electintpo_elecofffair electintpo_richbuy electintpo_votechc women_bond    women_bondea women_bondha women_bond_x women_works women_worksbetter women_worksworse women_works_x
    modsex_discamt modsex_media modsex_mediamore modsex_medialess modsex_media_x modsex_special    modsex_disc modsex_prob modsex_oppor modsex_menmore modsex_wommore modsex_oppor_x aapost_hire
    aapost_hire_oth aapost_hirefav aapost_hireopp aapost_hire_x auth_ind auth_cur auth_obed auth_consid    egal_equal egal_toofar egal_bigprob egal_worryless egal_notbigprob egal_fewerprobs wiretappo_toofar
    cog_opinions cog_opin cog_opinfew cog_opinmore cog_opin_x nonmain_born nonmain_endlife    nonmain_govt911 nonmain_bias nonmain_hurric cses_exphlth cses_expeduc cses_expunemp cses_expdef
    cses_expss cses_expbusind cses_exppolc cses_expwelf cses_impstdliv cses_econ cses_econb cses_econw    cses_govtact cses_diffpower cses_diffvote cses_dptylike cses_rptylike cses_rpclike cses_dpclike
    cses_dptyleft cses_rptyleft cses_selfleft cses_satisdem cses_closepty cses_ptymore cses_ptyclost    cses_ptyclost_oth cses_degclose cses_contct cses_ftf cses_mail cses_phone cses_txtmsg cses_email
    cses_socnet cses_ptycont_1st cses_ptycont_2nd cses_ptycont_3rd cses_ptycont_4th cses_ptycont_5th    cses_ptycont_dc cses_ptycont_rc cses_ptycont_dp cses_ptycont_rp cses_ptycont_othcont
    cses_ptycont_oth cses_ptycont_dkrf cses_persuade cses_persftf cses_persmail cses_persph    cses_perstxt cses_perseml cses_persweb cses_mobph cses_poliinfone cses_polinftwo_rate
    cses_polinftwo_date cses_polinftwo cses_poliinfthree cses_poliinffour cses_increduc cses_ownresid    cses_ownoth cses_ownstck cses_ownsavg cses_diffjob cses_spdiffjb dhs_threat dhs_threatamt
    dhs_appterr dhs_appterrmch dhs_disterrmch dhs_attack dhs_torture dhs_torturefav dhs_tortureopp    pohisp_hispnews pohisp_hispnews_oth pohisp_uselang pohisp_renglish pohisp_renglish_oth
    pohisp_rspanish pohisp_rspanish_oth pohisp_keepspan pohisp_readeng pohisp_speakeng pohisp_impassim    pohisp_impdistinct pohisp_cnctcntry pohisp_viscntry pohisp_moneycntry pohisp_polcntry
    pohisp_votecntry casistartpo_iwrset4 casistartpo_iwrset6 ftcasi_asian ftcasi_hisp ftcasi_black    ftcasi_illegal ftcasi_white racecasi_infwhite racecasi_infblacks racecasi_infhisp
    racecasi_sympblacks racecasi_admblacks ident_hispid ident_whiteid ident_blackid ident_nativeid    ident_asianid ident_pacifid ident_otherid ident_religid_preload ident_religid ident_amerid
    ineqinc_ineqgb ineqinc_ineqreduc stype_hwkwhite stype_hwkblack stype_hwkhisp stype_hwkasian    stype_intwhite stype_intblack stype_inthisp stype_intasian tipi_extra tipi_crit tipi_dep tipi_anx
    tipi_open tipi_resv tipi_warm tipi_disorg tipi_calm tipi_conv incpo_totinc incpo_totmiss40    incpo_totmiss20 incpo_totl20 incpo_totg20l40 incpo_totmiss70 incpo_totg40l70 incpo_totmiss100
    incpo_totg70l100 incpo_totg100 incgroup_prepost_x discrim_blacks discrim_hispanics discrim_whites    discrim_gays discrim_women discrim_self rstype_violcath rstype_violprot rstype_violmusl
    rstype_violmorm rstype_violnonrel rstype_patrcath rstype_patrmusl rstype_patrmorm rstype_patrprot    rstype_patrnonrel sample_state sample_stfips sample_region sample_district sample_district_prev
    sample_countyfips sample_countyname sample_ftf_replicate sample_ftf_advletdate sample_ftf_chumflag    sample_tract sample_ftf_timezone sample_web_statusmsa sample_web_cbsa sample_web_mktarea
    sample_ftf_zip admin_pre_ftf_iwdatebeg admin_pre_web1_iwdatebeg admin_pre_web2_iwdatebeg    admin_pre_ftf_iwbegtime admin_pre_web1_iwbegtime admin_pre_web2_iwbegtime 
    admin_pre_web1length admin_pre_web2length admin_pre_ftf_iwdatefin admin_pre_web1_iwdatefin    admin_pre_web2_iwdatefin admin_pre_ftf_iwfintime admin_pre_web1_iwfintime admin_pre_web2_iwfintime
    admin_pre_iwrecorded admin_pre_lang_start admin_pre_ltr_notif admin_pre_ltr_notifdate    admin_pre_ltr_refcon1 admin_pre_ltr_refcon1date admin_pre_ltr_refcon2 admin_pre_ltr_refcon2date
    admin_pre_ltr_lockedbldg admin_pre_ltr_lockedbldgdate admin_pre_ltr_nocont admin_pre_ltr_nocontdate    admin_post_ftf_iwdatebeg admin_post_web1_iwdatebeg admin_post_web2_iwdatebeg
    admin_post_ftf_iwbegtime admin_post_web1_iwbegtime admin_post_web2_iwbegtime admin_post_iwlength    admin_post_web1length admin_post_web2length admin_post_ftf_iwdatefin admin_post_web1_iwdatefin
    admin_post_web2_iwdatefin admin_post_ftf_iwfintime admin_post_web1_iwfintime    admin_post_web2_iwfintime admin_post_iwrecorded admin_post_lang_start admin_post_ltr_notif
    admin_post_ltr_notifdate admin_post_ltr_refcon admin_post_ltr_refcondate admin_post_ltr_nocont1    admin_post_ltr_nocont1date admin_post_ltr_nocontfin admin_post_ltr_nocontfindate hhlist_completed
    hhlist_attempts hhlist_datecompl hhlist_r_number hhlist_r_agegrp hhlist_r_age hhlist_r_hisp    hhlist_r_obshisp hhlist_r_black hhlist_r_obsblack hhlist_listtot hhlist_hhtot hhlist_elighhtot
    hhlist_hisphhtot hhlist_blackhhtot hhlist_person1_eligible hhlist_person1_whyinelig    hhlist_person1_resid hhlist_person1_agegrp hhlist_person1_agefull hhlist_person1_agemiss
    hhlist_person1_obs18 hhlist_person1_age18 hhlist_person1_citz hhlist_person1_hisp    hhlist_person1_obshisp hhlist_person1_black hhlist_person1_obsblack hhlist_person2_eligible
    hhlist_person2_whyinelig hhlist_person2_resid hhlist_person2_agegrp hhlist_person2_agefull    hhlist_person2_agemiss hhlist_person2_obs18 hhlist_person2_age18 hhlist_person2_citz
    hhlist_person2_hisp hhlist_person2_obshisp hhlist_person2_black hhlist_person2_obsblack    hhlist_person3_eligible hhlist_person3_whyinelig hhlist_person3_resid hhlist_person3_agegrp
    hhlist_person3_agefull hhlist_person3_agemiss hhlist_person3_obs18 hhlist_person3_age18    hhlist_person3_citz hhlist_person3_hisp hhlist_person3_obshisp hhlist_person3_black
    hhlist_person3_obsblack hhlist_person4_eligible hhlist_person4_whyinelig hhlist_person4_resid    hhlist_person4_agegrp hhlist_person4_agefull hhlist_person4_agemiss hhlist_person4_obs18
    hhlist_person4_age18 hhlist_person4_citz hhlist_person4_hisp hhlist_person4_obshisp    hhlist_person4_black hhlist_person4_obsblack hhlist_person5_eligible hhlist_person5_whyinelig
    hhlist_person5_resid hhlist_person5_agegrp hhlist_person5_agefull hhlist_person5_agemiss    hhlist_person5_obs18 hhlist_person5_age18 hhlist_person5_citz hhlist_person5_hisp
    hhlist_person5_obshisp hhlist_person5_black hhlist_person5_obsblack hhlist_person6_eligible    hhlist_person6_whyinelig hhlist_person6_resid hhlist_person6_agegrp hhlist_person6_agefull
    hhlist_person6_agemiss hhlist_person6_obs18 hhlist_person6_age18 hhlist_person6_citz    hhlist_person6_hisp hhlist_person6_obshisp hhlist_person6_black hhlist_person6_obsblack
    hhlist_person7_eligible hhlist_person7_whyinelig hhlist_person7_resid hhlist_person7_agegrp    hhlist_person7_agefull hhlist_person7_agemiss hhlist_person7_obs18 hhlist_person7_age18
    hhlist_person7_citz hhlist_person7_hisp hhlist_person7_obshisp hhlist_person7_black    hhlist_person7_obsblack hhlist_iwrid dwell_completed dwell_datecompl dwell_winsign
    dwell_winsign_dsc dwell_frontsign dwell_frontsign_dsc dwell_sign_dpc dwell_sign_rpc dwell_relig    dwell_religmsg_spec dwell_secur_mention1 dwell_secur_mention2 dwell_secur_mention3
    dwell_secur_mention4 dwell_secur_mention5 dwell_structure dwell_structure_oth dwell_strctsize    dwell_strctsize_oth dwell_structresid dwell_block_urban dwell_block_resid dwell_block_resid_oth
    dwell_hu_cond_mention1 dwell_hu_cond_mention2 dwell_hu_cond_mention3 dwell_hu_cond_mention4    dwell_hu_cond_mention5 dwell_hu_cond_mention6 dwell_hu_cond_mention7 dwell_hu_cond_mention8
    dwell_hu_cond_mention9 dwell_hu_cond_mention10 dwell_area_cond_mention1 dwell_area_cond_mention2    dwell_area_cond_mention3 dwell_area_cond_mention4 dwell_area_cond_mention5 dwell_area_cond_mention6
    dwell_bldg_relcond dwell_iwrid recontact_completed recontact_rname_given recontact_sampaddr_correct    recontact_newaddr_given recontact_addr_err recontact_phone_given recontact_have2ndphone
    recontact_haveemail recontact_setappt recontact_setappt_date recontact_refreason    recontact_c1_name_given recontact_c1_relshp recontact_c1_addr_given recontact_c1_phone_given
    recontact_c1_haveothph recontact_c1_haveemail recontact_c2_name_given recontact_c2_relshp    recontact_c2_addr_given recontact_c2_phone_given recontact_c2_haveothph recontact_c2_haveemail
    recontact_iwrid iwrobspre_completed iwrobspre_skintone iwrobspre_winsigns iwrobspre_winsigns_dsc    iwrobspre_frontsigns iwrobspre_frontsigns_dsc iwrobspre_sign_dpc iwrobspre_sign_rpc
    iwrobspre_othpresent1 iwrobspre_othpresent2 iwrobspre_othpresent3 iwrobspre_othpresent4    iwrobspre_othpresent5 iwrobspre_othpresent6 iwrobspre_coop iwrobspre_levinfo iwrobspre_intell
    iwrobspre_suspic iwrobspre_interest iwrobspre_sincere iwrobspre_doubtsnc iwrobspre_doubtsnc_dsc    iwrobspre_estinc iwrobspre_estage iwrobspre_gender iwrobspre_esteduc iwrobspre_esteduc_oth
    iwrobspre_react1 iwrobspre_react2 iwrobspre_react3 iwrobspre_react4 iwrobspre_react5    iwrobspre_react6 iwrobspre_react7 iwrobspre_react8 iwrobspre_react9 iwrobspre_iwrentry_casi
    iwrobspre_iwraid_casi1 iwrobspre_iwraid_casi2 iwrobspre_iwraid_casi3 iwrobspre_datecompl    iwrobspre_iwrid iwrobspost_completed iwrobspost_othpresent1 iwrobspost_othpresent2
    iwrobspost_othpresent3 iwrobspost_othpresent4 iwrobspost_othpresent5 iwrobspost_othpresent6    iwrobspost_coop iwrobspost_levinfo iwrobspost_intell iwrobspost_suspic iwrobspost_interest
    iwrobspost_sincere iwrobspost_doubtsnc iwrobspost_doubtsnc_dsc iwrobspost_react1 iwrobspost_react2    iwrobspost_react3 iwrobspost_react4 iwrobspost_react5 iwrobspost_react6 iwrobspost_react7
    iwrobspost_react8 iwrobspost_iwrentry_casi iwrobspost_iwraid_casi iwrobspost_datecompl    iwrobspost_iwrid iwrdesc_pre_completed iwrdesc_pre_iwrid iwrdesc_pre_skintone iwrdesc_pre_born_year
    iwrdesc_pre_age iwrdesc_pre_agegrp iwrdesc_pre_educ iwrdesc_pre_educgrp iwrdesc_pre_gender    iwrdesc_pre_lang iwrdesc_pre_exper iwrdesc_pre_exper_grp iwrdesc_pre_hisp iwrdesc_pre_race_white
    iwrdesc_pre_race_black iwrdesc_pre_race_other iwrdesc_pre_race_native iwrdesc_pre_race_asian    iwrdesc_pre_race_pacif iwrdesc_pre_race_oth iwrdesc_pre_pid iwrdesc_pre_pid_demstr
    iwrdesc_pre_pid_repstr iwrdesc_pre_pid_lean iwrdesc_post_completed iwrdesc_post_iwrid    iwrdesc_post_skintone iwrdesc_post_born_year iwrdesc_post_age iwrdesc_post_agegrp iwrdesc_post_educ
    iwrdesc_post_educgrp iwrdesc_post_gender iwrdesc_post_lang iwrdesc_post_exper    iwrdesc_post_exper_grp iwrdesc_post_hisp iwrdesc_post_race_white iwrdesc_post_race_black
    iwrdesc_post_race_other iwrdesc_post_racenative iwrdesc_post_raceasian iwrdesc_post_racepacif    iwrdesc_post_race_oth iwrdesc_post_pid iwrdesc_post_pid_demstr iwrdesc_post_pid_repstr
    iwrdesc_post_pid_lean profile_completed profile_panelentrydate profile_recruittype     profile_headhh profile_hhsize profile_housing profile_homeown
    profile_educdegree profile_educ profile_region9 profile_hhchild0to1 profile_hhchild2to5    profile_hhchild6to12 profile_hhchild13to17 profile_hhchild0to5_x profile_hhchild6to17_x
    profile_hhadults profile_raceeth profile_gender profile_marital profile_hhincome profile_empstatus    profile_inetaccess profile_pid7_x profile_hhmembers profile_race_r profile_racefull_r
    profile_censusrace_r profile_censusracefull_r profile_hisp profile_lang profile_preferlang    profile_primelang profile_spanspeak profile_spanread profile_engspeak profile_engread profile_race1
    profile_race2 profile_race3 profile_racemost profile_racemost_full profile_spanishsurv    profile_trynewprod profile_newbrands profile_looknewprod profile_trynew1st profile_tellothersnew
    profile_hhshopamt profile_rparentguard profile_emptynext profile_everparent profile_hhlandline    profile_hhcellphone profile_phoneuse profile_computers profile_inetcomputers profile_inet_dialup
    profile_inet_dsl profile_inet_cable profile_inet_bband profile_inet_satell profile_inet_fiboptics    profile_inet_tohbband profile_inet_wireless profile_inet_other profile_birthmonth profile_birthday
    profile_birthyear profile_rpet_cat profile_rpet_dog profile_rpet_fish profile_rpet_bird    profile_rpet_gerbil profile_rpet_reptile profile_rpet_horse profile_rpet_other profile_oth_hhpet
    profile_rstudent profile_dualincome profile_numjobs profile_fulltimejob profile_jobind    profile_ind_foodmfg profile_ind_bevtob profile_ind_pharm profile_ind_healthprod profile_ind_hhprod
    profile_ind_advert profile_ind_healthcare profile_ind_mktresearch profile_ind_marketing    profile_ind_pubrel profile_ind_broadcast profile_ind_finance profile_ind_retail profile_ind_foodbev
    profile_occ1current profile_occ2current profile_occ3current profile_employersize profile_occ1recent    profile_occ2recent profile_occ3recent profile_hhpurchdec paprofile_lang paprofile_righttrack
    paprofile_mip paprofile_mip_oth paprofile_regist paprofile_everreg paprofile_vote2008_pres    paprofile_howvote2008_pres paprofile_pres2008_oth paprofile_vote2010_congr
    paprofile_howvote2010_congr paprofile_pid paprofile_othpid paprofile_pidstrong_rep    paprofile_pidstrong_dem paprofile_pidcloser paprofile_libcon_self paprofile_libcon_pres
    paprofile_favrate_pres paprofile_presperf paprofile_presperf_econ paprofile_presperf_deficit    paprofile_presperf_healthc paprofile_presperf_taxes paprofile_presperf_educ
    paprofile_presperf_forgnpol paprofile_presperf_racerel paprofile_presperf_envir    paprofile_presperf_immig paprofile_presperf_terror paprofile_presperf_afghan
    paprofile_presperf_jobs paprofile_presperf_energy paprofile_prestime_forgnpol    paprofile_prestime_economic paprofile_prestime_domestic paprofile_prestime_homesec
    paprofile_interestpolit paprofile_freqpolit_work paprofile_freqpolit_church    paprofile_freqpolit_friends paprofile_freqpolit_family paprofile_freqpolit_blog
    paprofile_freqpolit_socmedia paprofile_politinfo_radio paprofile_politinfo_inetnews    paprofile_politinfo_prntnwsp paprofile_politinfo_tv paprofile_politinfo_mags
    paprofile_politinfo_blogs paprofile_politinfo_socmedia paprofile_ancestry_1 paprofile_ancestry_2    paprofile_ancestry_3 paprofile_ancestry_4 paprofile_ancestry_5 paprofile_rlang_1 paprofile_rlang_2
    paprofile_rlang_3 paprofile_otherslang_1 paprofile_otherslang_2 paprofile_otherslang_3    paprofile_borncit paprofile_whencit paprofile_priorcit paprofile_multcit paprofile_2ndcit
    paprofile_orient_r paprofile_orient_oth paprofile_transgender paprofile_unionmem paprofile_aarp    paprofile_milit paprofile_milit_family paprofile_religion paprofile_religionfull
    paprofile_religion_oth paprofile_bornagain paprofile_jewish paprofile_jewishparent paprofile_attend    paprofile_orgservice paprofile_orgveterans paprofile_orgrelig paprofile_orgsenior
    paprofile_orgwomen paprofile_orgpolitiss paprofile_orgcivic paprofile_orgschool paprofile_orgyouth    paprofile_orgneighb paprofile_orgethnic paprofile_attendpta paprofile_attendcommun
    paprofile_donateblood paprofile_givecharity paprofile_workcharity paprofile_rally    paprofile_govtoffic paprofile_prescamp paprofile_othcamp paprofile_moneyprescamp
    paprofile_moneyothcamp paprofile_workcommuniss paprofile_workcommbd paprofile_lettertonewsp    paprofile_messagebd paprofile_publicofc paprofile_1stcamp paprofile_active_teapty
    paprofile_active_envir paprofile_active_womrts paprofile_active_equrts paprofile_active_righttolife    paprofile_active_peace paprofile_active_lgbt paprofile_active_occupy paprofile_recent_teapty
    paprofile_recent_envir paprofile_recent_womrts paprofile_recent_equrts paprofile_recent_righttolife    paprofile_recent_peace paprofile_recent_lgbt paprofile_recent_occupy paprofile_moneyenvir
    paprofile_timeenvir paprofile_recyclepaper paprofile_recyclecans paprofile_recycleglass    paprofile_recycleplast paprofile_prodrecycled paprofile_energycut paprofile_replacebulbs
    paprofile_otherenvir paprofile_engytaxcredit paprofile_selfenvironlst paprofile_hhguns    paprofile_pistol paprofile_shotgun paprofile_rifle paprofile_othergun paprofile_othergun_type
    paprofile_personalgun paprofile_comments race2012_sen race2012_gov typerace2012_hse    typerace2012_sen typerace2012_gov cand_hse_dem_name cand_hse_dem_gend cand_hse_dem_code
    cand_hse_rep_name cand_hse_rep_gend cand_hse_rep_code cand_hse_oth_name cand_hse_oth_gend    cand_hse_oth_code cand_hse_oth_pty cand_sen_dem_name cand_sen_dem_gend cand_sen_dem_code
    cand_sen_rep_name cand_sen_rep_gend cand_sen_rep_code cand_sen_oth_name cand_sen_oth_gend    cand_sen_oth_code cand_sen_oth_pty sen_norace_srsen_name sen_norace_srsen_pty sen_norace_srsen_gend
    sen_norace_srsen_code sen_norace_jrsen_name sen_norace_jrsen_pty sen_norace_jrsen_gend    sen_norace_jrsen_code sen_race_sennotup_name sen_race_sennotup_pty sen_race_sennotup_gend
    sen_race_sennotup_code cand_gov_dem_name cand_gov_dem_gend cand_gov_dem_code cand_gov_rep_name    cand_gov_rep_gend cand_gov_rep_code cand_gov_oth_name cand_gov_oth_gend cand_gov_oth_code
    cand_gov_oth_pty hserep_before_electn_name hserep_before_electn_pty hserep_before_electn_gend    randordq_medsrc_tvprog_01 randordq_medsrc_tvprog_02 randordq_medsrc_tvprog_03
    randordq_medsrc_tvprog_04 randordq_medsrc_tvprog_05 randordq_medsrc_tvprog_06    randordq_medsrc_tvprog_07 randordq_medsrc_tvprog_08 randordq_medsrc_tvprog_09
    randordq_medsrc_tvprog_10 randordq_medsrc_tvprog_11 randordq_medsrc_tvprog_12    randordq_medsrc_tvprog_13 randordq_medsrc_tvprog_14 randordq_medsrc_tvprog_15
    randordq_medsrc_tvprog_16 randordq_medsrc_tvprog_17 randordq_medsrc_tvprog_18    randordq_medsrc_tvprog_19 randordq_medsrc_tvprog_20 randordq_medsrc_tvprog_21
    randordq_medsrc_tvprog_22 randordq_medsrc_tvprog_23 randordq_medsrc_tvprog_24    randordq_medsrc_tvprog_25 randordq_medsrc_tvprog_26 randordq_medsrc_tvprog_27
    randordq_medsrc_tvprog_28 randordq_medsrc_tvprog_29 randordq_medsrc_tvprog_30    randordq_medsrc_tvprog_31 randordq_medsrc_tvprog_32 randordq_medsrc_tvprog_33
    randordq_medsrc_tvprog_34 randordq_medsrc_tvprog_35 randordq_medsrc_tvprog_36    randordq_medsrc_tvprog_37 randordq_medsrc_tvprog_38 randordq_medsrc_tvprog_39
    randordq_medsrc_tvprog_40 randordq_medsrc_tvprog_41 randordq_medsrc_tvprog_42    randordq_medsrc_tvprog_43 randordq_medsrc_tvprog_44 randordq_medsrc_tvprog_45
    randordq_medsrc_tvprog_46 randordq_medsrc_tvprog_47 randordq_medsrc_tvprog_48    randordq_medsrc_tvprog_49 randordq_medsrc_tvprog_50 randordq_medsrc_tvprog_51
    randordq_medsrc_tvprog_52 randordq_medsrc_tvprog_53 randordq_medsrc_tvprog_54    randordq_medsrc_tvprog_55 randordq_medsrc_tvprog_56 randordq_medsrc_tvprog_57
    randordq_medsrc_tvprog_58 randordq_medsrc_tvprog_59 randordq_medsrc_tvprog_60    randordq_medsrc_tvprog_61 randordq_medsrc_tvprog_62 randordq_medsrc_tvprog_63
    randordq_medsrc_tvprog_64 randord_medsrc_tvprog01_scrn randord_medsrc_tvprog02_scrn    randord_medsrc_tvprog03_scrn randord_medsrc_tvprog04_scrn randord_medsrc_tvprog05_scrn
    randord_medsrc_tvprog06_scrn randord_medsrc_tvprog07_scrn randord_medsrc_tvprog08_scrn    randord_medsrc_tvprog09_scrn randord_medsrc_tvprog10_scrn randord_medsrc_tvprog11_scrn
    randord_medsrc_tvprog12_scrn randord_medsrc_tvprog13_scrn randord_medsrc_tvprog14_scrn    randord_medsrc_tvprog15_scrn randord_medsrc_tvprog16_scrn randord_medsrc_tvprog17_scrn
    randord_medsrc_tvprog18_scrn randord_medsrc_tvprog19_scrn randord_medsrc_tvprog20_scrn    randord_medsrc_tvprog21_scrn randord_medsrc_tvprog22_scrn randord_medsrc_tvprog23_scrn
    randord_medsrc_tvprog24_scrn randord_medsrc_tvprog25_scrn randord_medsrc_tvprog26_scrn    randord_medsrc_tvprog27_scrn randord_medsrc_tvprog28_scrn randord_medsrc_tvprog29_scrn
    randord_medsrc_tvprog30_scrn randord_medsrc_tvprog31_scrn randord_medsrc_tvprog32_scrn    randord_medsrc_tvprog33_scrn randord_medsrc_tvprog34_scrn randord_medsrc_tvprog35_scrn
    randord_medsrc_tvprog36_scrn randord_medsrc_tvprog37_scrn randord_medsrc_tvprog38_scrn    randord_medsrc_tvprog39_scrn randord_medsrc_tvprog40_scrn randord_medsrc_tvprog41_scrn
    randord_medsrc_tvprog42_scrn randord_medsrc_tvprog43_scrn randord_medsrc_tvprog44_scrn    randord_medsrc_tvprog45_scrn randord_medsrc_tvprog46_scrn randord_medsrc_tvprog47_scrn
    randord_medsrc_tvprog48_scrn randord_medsrc_tvprog49_scrn randord_medsrc_tvprog50_scrn    randord_medsrc_tvprog51_scrn randord_medsrc_tvprog52_scrn randord_medsrc_tvprog53_scrn
    randord_medsrc_tvprog54_scrn randord_medsrc_tvprog55_scrn randord_medsrc_tvprog56_scrn    randord_medsrc_tvprog57_scrn randord_medsrc_tvprog58_scrn randord_medsrc_tvprog59_scrn
    randord_medsrc_tvprog60_scrn randord_medsrc_tvprog61_scrn randord_medsrc_tvprog62_scrn    randord_medsrc_tvprog63_scrn randord_medsrc_tvprog64_scrn randordq_medsrc_radio_01
    randordq_medsrc_radio_02 randordq_medsrc_radio_03 randordq_medsrc_radio_04 randordq_medsrc_radio_05    randordq_medsrc_radio_06 randordq_medsrc_radio_07 randordq_medsrc_radio_08 randordq_medsrc_radio_09
    randordq_medsrc_radio_10 randordq_medsrc_radio_11 randordq_medsrc_radio_12 randordq_medsrc_radio_13    randordq_medsrc_radio_14 randordq_medsrc_radio_15 randordq_medsrc_websites_01
    randordq_medsrc_websites_02 randordq_medsrc_websites_03 randordq_medsrc_websites_04    randordq_medsrc_websites_05 randordq_medsrc_websites_06 randordq_medsrc_websites_07
    randordq_medsrc_websites_08 randordq_medsrc_websites_09 randordq_medsrc_websites_10    randordq_medsrc_websites_11 randordq_medsrc_websites_12 randordq_medsrc_websites_13
    randordq_medsrc_websites_14 randordq_medsrc_websites_15 randordq_medsrc_newsp_01    randordq_medsrc_newsp_02 randordq_medsrc_newsp_03 randordq_medsrc_newsp_04 randordq_medsrc_newsp_05
    randordq_medsrc_newsp_06 randordq_medsrc_newsp_07 randordq_medsrc_newsp_08 randordq_medsrc_newsp_09    randordq_medsrc_newsp_10 randordq_medsrc_newsp_11 randordq_medsrc_newsp_12 randordq_medsrc_newsp_13
    randordq_medsrc_newsp_14 randordq_medsrc_newsp_15 randsplice_revisedstandard randopts_fwdrev    randordq_cands_parties randord_vote_ptynames randordq_web_pretherms randordq_affects
    rand_place_likelypercent randordq_ecblame_pres randordq_ecblame_prevpres randordq_ecblame_congdem    randordq_ecblame_congrep randordq_ecblame_wallstr randordq_ecblame_consumers
    randordq_ecblame_lenders randord_econperf_ptynames randsplice_dutychoice randord_pid_ptynames    randordq_trait_moral randordq_trait_strong randordq_trait_cares randordq_trait_know
    randordq_trait_intell randordq_trait_honest randsplice_fedspendtxt randordq_fedspend_socsec    randordq_fedspend_pubsch randordq_fedspend_scitech randordq_fedspend_crime
    randordq_fedspend_welfare randordq_fedspend_child randordq_fedspend_poor randordq_fedspend_envir    randopts_pk_medicare randopts_pk_spendleast randord_womenperf_ptynames randordq_ftf_thermpo_pcpcsp
    randordq_web_thermpopc randordq_web_thermpopcsp randordq_thermpo_hscand    randordq_web_thermpo_sencand randordq_web_thermpo_senatrs randordq_web_thermpo_vpc
    randordq_grptherm_xfund randordq_grptherm_cath randordq_grptherm_feminst randordq_grptherm_fedgov    randordq_grptherm_lib randordq_grptherm_midclass randordq_grptherm_labor randordq_grptherm_poor
    randordq_grptherm_milit randordq_grptherm_bigbusn randordq_grptherm_welfare    randordq_grptherm_conserv randordq_grptherm_wkclass randordq_grptherm_suprct
    randordq_grptherm_gaylesb randordq_grptherm_congress randordq_grptherm_rich    randordq_grptherm_muslim randordq_grptherm_xtian randordq_grptherm_atheist randordq_grptherm_mormon
    randordq_grptherm_teapty randord_mip_ptynames randordq_deficit_inctax randordq_deficit_medvouch    randordq_deficit_corptax randordq_deficit_cutmilit randordq_deficit_fedemp randordq_deficit_cutgovt
    randordq_ftf_abort_pc randordq_abort_healthnonfatl randordq_abort_healthfatal randordq_abort_incest    randordq_abort_rape randordq_abort_defect randordq_abort_financial randordq_abort_gendpref
    randord_factor_pcnamestxt randordq_factor_rpcreligion randordq_factor_dpcrace    randordq_factor_hcarelaw randordq_factor_economy randordq_factor_foreignpol
    randordq_factor_dpcreligion randordq_factor_rpcwealth randordq_factor_dpcparty    randordq_factor_rpcparty randopts_pk_secytreas randopts_pk_pty2ndhse randopts_pk_secyun
    randordq_casitherm_asianam randordq_casitherm_hisp randordq_casitherm_black    randordq_casitherm_illegal randordq_casitherm_white randordq_stereogroups randordq_discrim_black
    randordq_discrim_hisp randordq_discrim_white randordq_discrim_gay randordq_discrim_women    randordq_stereorelig invited_inetrecontact2013 Year
  /COMPRESSED.

DATASET CLOSE DataSet2.
EXE.

GET
  FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 Analysis/anes_timeseries_2012_truncated for merge.sav'.
DATASET NAME DataSet3 WINDOW=FRONT.

ALTER TYPE VCF0006a (F8).
EXECUTE.

DATASET ACTIVATE DataSet1.
STAR JOIN
  /SELECT *
  /FROM * AS t0
  /JOIN 'DataSet3' AS t1
    ON t0.VCF0006a=t1.VCF0006a
  /OUTFILE FILE=*.

DATASET CLOSE DataSet3.
EXE.

DESCRIPTIVES dem2_inethome
dem2_landline
dem2_cellnum
inc_incgroup_pre
admin_pre_iwlength.

*2016

GET
  FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 Analysis/anes_timeseries_2016.sav'.
DATASET NAME DataSet4 WINDOW=FRONT.

DESCRIPTIVES V160001.
EXE.
STRING Zero (A1).
STRING Zero2 (A2).
STRING Zero3 (A3).
COMPUTE Zero = '0'.
COMPUTE Zero2='00'.
COMPUTE Zero3 = '000'.
EXE.

COMPUTE caseidb = V160001.
ALTER TYPE caseidb (F4).
ALTER TYPE caseidb (A4).
EXECUTE.

STRING caseid1 caseid2 caseid3(A4).
COMPUTE caseid3 = concat(Zero3, LTRIM(caseidb)).
COMPUTE caseid2 = concat(Zero2, LTRIM(caseidb)).
COMPUTE caseid1 = concat(Zero, LTRIM(caseidb)).
EXE.

STRING CaseidFinal (A4).
IF (V160001  LT 10) CaseidFinal = caseid3.
IF (V160001  GT 9 AND V160001 LT 100) CaseidFinal = caseid2.
IF (V160001  GT 99 AND V160001 LT 1000) CaseidFinal = caseid1.
IF (V160001 GT 999) CaseidFinal = caseidb.
EXE.

STRING VCF0006a (A8).
EXE.
STRING Year (A4).
EXECUTE.
COMPUTE Year = "2016".
EXE.
COMPUTE VCF0006a = concat(Year,CaseidFinal).
EXE.
ALTER TYPE VCF0006a (F8).
EXE.

DELETE VARIABLES Zero Zero2 Zero3 caseidb caseid1
caseid2 caseid3 CaseidFinal.
EXE.

Freq V161511.

*KEEP 
VCF0006a V161361x V164006 V161326 V161328 V161327
V161497 V161498 V161499 V161500
V161501 V161502 V161503 V161504 V161505 V161506

SAVE OUTFILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 '+
    'Analysis/anes_timeseries_2016_truncated for merge.sav'
  /DROP=version V160001 V160001_orig V160101 V160101f V160101w V160102 V160102f V160102w V160201    V160201f V160201w V160202 V160202f V160202w V160501 V160502 V161001 V161002 V161003 V161004 V161005
    V161006 V161007 V161008 V161009 V161010a V161010b V161010c V161010d V161010e V161010f V161011    V161011a V161012 V161013a V161013b V161014 V161015a V161015b V161015c V161015d V161015e V161016
    V161017 V161018 V161019 V161020 V161021 V161021a V161022 V161022a V161023 V161024x V161025 V161025a    V161025x V161026 V161027 V161028 V161029a V161029b V161030 V161031 V161032 V161033 V161034 V161035
    V161036 V161037 V161038 V161039 V161040 V161041 V161042 V161043 V161044 V161045x V161046 V161047    V161048 V161049 V161050 V161051 V161052 V161053 V161054 V161055 V161056 V161057 V161058 V161059
    V161060 V161061 V161062 V161063 V161064x V161065x V161066x V161067x V161068 V161069 V161070a    V161071 V161072 V161073a V161074 V161075 V161076a V161077 V161078 V161079a V161080 V161080a
    V161080x V161081 V161082 V161082a V161082x V161083 V161083a V161083x V161084 V161084a V161084x    V161085 V161085a V161085x V161086 V161087 V161088 V161089 V161090 V161091 V161092 V161093 V161094
    V161095 V161096 V161097 V161098 V161099a V161100 V161101 V161102a V161103 V161104 V161105a V161106    V161107 V161108a V161109 V161110 V161111 V161112 V161113 V161114a V161114b V161114x V161115 V161116
    V161117 V161118 V161119 V161120 V161121 V161122 V161123 V161124 V161125 V161126 V161127 V161128    V161129 V161130 V161131 V161132 V161133 V161134a V161134b V161135a V161135b V161136 V161137
    V161138a V161138b V161138x V161139 V161140 V161140a V161140x V161141 V161141a V161141x V161142    V161142a V161142x V161143 V161144 V161145 V161146 V161147 V161148 V161149 V161150a V161150b
    V161151a V161151b V161151x V161152 V161153 V161154 V161155 V161155a V161156 V161157 V161158x    V161159 V161160 V161161 V161162 V161163 V161164 V161165 V161166 V161167 V161168 V161169 V161170
    V161171 V161172 V161173 V161174 V161175 V161176 V161177 V161178 V161179 V161180 V161181 V161182    V161183 V161184 V161185 V161186 V161187 V161188 V161189 V161190 V161191 V161192 V161193 V161193a
    V161194x V161195 V161195a V161195x V161196 V161196a V161196x V161197 V161198 V161199 V161200    V161201 V161202 V161203 V161204 V161204a V161204b V161204x V161205 V161206 V161207 V161208 V161209
    V161210 V161211 V161212 V161213 V161213a V161213x V161214 V161214a V161214x V161215 V161216 V161217    V161218 V161219 V161220 V161221 V161222 V161223 V161224 V161224a V161225x V161226 V161226a V161226x
    V161227 V161227a V161227x V161228 V161228a V161228x V161229 V161229a V161229x V161230 V161231    V161232 V161233 V161233a V161233x V161234 V161235 V161235a V161235x V161236 V161237 V161238
    V161239a V161239b V161240a V161240b V161241 V161242 V161243 V161244 V161245 V161245a V161246    V161247a V161247b V161248 V161249 V161250 V161251 V161252 V161253 V161254 V161255 V161256 V161257
    V161258 V161259 V161260 V161261 V161262a V161262b V161263 V161264x V161265x V161266a V161266b    V161266c V161266d V161266e V161266f V161266g V161266h V161266j V161266k V161266m V161266n V161266p
    V161267 V161267a V161267b V161267c V161267x V161268 V161269 V161270 V161271 V161272 V161273    V161274a V161274b V161275x V161276x V161277 V161278 V161279 V161280a V161280b V161280c V161281
    V161282a V161282b V161283a V161283b V161284 V161285 V161286 V161287 V161288 V161289 V161290    V161291a V161291b V161292a V161292b V161293 V161294 V161295 V161296 V161297 V161298 V161299
    V161300a V161300b V161300c V161300d V161300e V161300f V161300g V161301a V161301b V161302 V161303    V161304 V161305a V161305b V161306 V161307 V161307a V161308x V161309 V161310a V161310b V161310c
    V161310d V161310e V161310f V161310g V161310x V161311 V161312a V161313 V161314 V161314a V161315    V161316 V161317 V161318 V161319 V161319x V161320 V161321 V161321a V161322 V161322a V161323 V161324
    V161325a V161325b V161325c V161325d V161325e    V161329 V161330 V161331a    V161331b V161331x V161332 V161333 V161334 V161335 V161335a V161336 V161337 V161338 V161339 V161340
    V161341 V161342 V161342a V161343 V161344 V161345 V161346 V161347 V161348 V161349 V161350 V161351    V161352 V161353 V161354 V161355 V161356 V161357 V161358 V161359 V161360  V161362 V161363a
    V161363b V161363c V161363d V161363e V161363f V161364 V161365 V161366 V161367 V161368 V161369    V161370 V161371 V161372 V161373 V161374 V161375 V161376 V161377 V161378 V161379 V161380 V161381
    V161382 V161383 V161384 V161385 V161386 V161387 V161388 V161389 V161390 V161391 V161392 V161393    V161394 V161395 V161396 V161397 V161398 V161399 V161400 V161401 V161402 V161403 V161404 V161405
    V161406 V161407 V161408 V161409 V161410 V161411 V161412 V161413 V161414 V161415 V161416 V161417    V161418 V161419 V161420 V161421 V161422 V161423 V161424 V161425 V161426 V161427 V161428 V161429
    V161430 V161431 V161432 V161433 V161434 V161435 V161436 V161437 V161438 V161439 V161440 V161441    V161442 V161443 V161444 V161445 V161446 V161447 V161448 V161449 V161450 V161451 V161452 V161453
    V161454 V161455 V161456 V161457 V161458 V161459 V161460 V161461x V161462 V161463 V161464 V161465    V161466 V161467 V161468 V161469 V161470 V161471 V161472 V161473 V161474 V161475 V161476 V161477
    V161478 V161479 V161480 V161481 V161482 V161483 V161484 V161485 V161486 V161487 V161488 V161489    V161490 V161491 V161492 V161493 V161494 V161495 V161496  V161507 V161508 V161509 V161510 V161511 V161512 V161513
    V161514 V161515 V161516 V161517 V161518 V161519 V161520 V161521 V161522 V161523 V162001 V162002    V162003 V162004 V162005 V162006 V162007 V162007a V162008 V162009 V162010 V162011 V162012 V162013
    V162014 V162014a V162014b V162016 V162016a V162016b V162017 V162018a V162018b V162018c V162018d    V162018e V162019 V162020a V162020c V162020b V162020d V162021a V162021b V162021c V162022 V162022a
    V162023 V162024a V162024b V162025 V162026a V162026b V162026c V162026d V162026e V162027 V162028    V162028x V162029 V162029x V162030 V162030x V162031 V162031x V162032x V162033 V162033a V162033x
    V162034 V162034a V162035 V162036 V162036a V162037 V162037a V162038 V162038x V162039 V162040 V162041    V162042 V162043 V162044 V162045x V162046 V162047 V162048 V162049 V162050 V162051 V162052 V162053
    V162054 V162055 V162056 V162057 V162058x V162059x V162060x V162061x V162062x V162063x V162064x    V162065x V162066x V162067x V162068x V162069x V162070a V162070b V162070c V162070d V162070e V162070f
    V162070g V162070h V162070i V162070j V162071 V162072 V162073a V162073b V162074a V162074b V162075a    V162075b V162076a V162076b V162078 V162079 V162080 V162081 V162082 V162083 V162084 V162085 V162086
    V162087 V162088 V162089 V162090 V162091 V162092 V162093 V162094 V162095 V162096 V162097 V162098    V162099 V162100 V162101 V162102 V162103 V162104 V162105 V162106 V162107 V162108 V162109 V162110
    V162111 V162112 V162113 V162114 V162114a V162114b V162114x V162115 V162116a V162116a_1 V162116a_2    V162116a_3 V162116a_4 V162116a_5 V162116a_6 V162116a_7 V162116a_8 V162116a_9 V162116a_10 V162117
    V162118a V162118a_1 V162118a_2 V162118a_3 V162118a_4 V162118a_5 V162118a_6 V162118a_7 V162118a_8    V162118a_9 V162119 V162120a V162120a_1 V162120a_2 V162120a_3 V162120a_4 V162120a_5 V162120a_6
    V162121 V162122a V162122a_1 V162122a_2 V162122a_3 V162122a_4 V162122a_5 V162123 V162124 V162125    V162125x V162126 V162127 V162128 V162129 V162130 V162131 V162132 V162133 V162134 V162135 V162136
    V162136x V162137 V162138 V162139 V162140 V162141 V162142 V162143 V162144 V162145 V162146 V162147    V162147x V162148 V162149 V162150 V162150x V162151 V162152a V162152b V162153 V162154a V162154b
    V162155a V162155b V162155x V162156x V162157 V162158 V162159 V162160 V162161 V162162 V162162x    V162163 V162164 V162165 V162166 V162167 V162168 V162169 V162170 V162171 V162171a V162172 V162173
    V162174 V162174a V162175 V162176 V162176a V162176x V162177 V162178 V162179 V162180 V162180a    V162180x V162181 V162182 V162183 V162184 V162185 V162186 V162188 V162188a V162188x V162189 V162189a
    V162189x V162190 V162191 V162191a V162192 V162193 V162193a V162193x V162194 V162195 V162196 V162197    V162198 V162199a V162200 V162201a V162202 V162203a V162204 V162205a V162207 V162208 V162209 V162210
    V162211 V162212 V162213 V162214 V162215 V162216 V162217 V162218 V162219 V162220 V162221 V162222    V162223 V162224 V162225 V162226 V162227 V162228 V162229a V162229b V162229x V162230 V162230a
    V162230b V162230x V162231 V162231a V162231b V162231x V162232 V162233 V162234 V162235 V162236    V162238 V162238a V162238b V162238x V162239 V162240 V162241 V162242 V162243 V162244 V162245 V162246
    V162248 V162249 V162250 V162251 V162252 V162253 V162253x V162254 V162255 V162255a V162255x V162256    V162257 V162258 V162259 V162260 V162261 V162262 V162263 V162264 V162265 V162266 V162267 V162268
    V162269 V162270 V162271 V162272 V162273 V162274 V162275 V162276 V162277 V162278 V162279 V162280    V162281 V162282 V162283 V162284 V162285 V162286 V162287 V162288 V162289 V162290 V162291 V162292a
    V162293 V162292b V162294 V162295 V162295a V162295b V162295x V162296a V162296b V162296c V162296x    V162297 V162298 V162299 V162299a V162300 V162301 V162302 V162303 V162304 V162305 V162306 V162307
    V162308 V162309x V162310 V162311 V162312 V162313 V162314 V162316 V162317 V162318 V162319 V162320    V162321 V162322 V162323 V162324 V162325 V162326 V162327 V162328 V162329 V162330 V162331 V162332
    V162333 V162334 V162335 V162336 V162337 V162338 V162339 V162340 V162341 V162342 V162343 V162344    V162345 V162346 V162347 V162348 V162349 V162350 V162351 V162352 V162353 V162354 V162355 V162356
    V162357 V162358 V162359 V162360 V162361 V162362 V162363 V162364 V162365 V162366 V162367 V162368    V162369 V162370 V162371a V162371b V163001a V163001b V163002 V164001a V164001b V164001c V164001d
    V164002 V164002a V164003 V164003a V164004 V164005  V164007 V164008 V164009 V164010 V164011    V164012 V164013 V165001a V165001b V165001c V165001d V165002 V165002a V165003 V165003a V165004
    V165005 V165006 V165007 V165008 V165009 V165500 V165501 V165502 V165503 V165504 V165505 V165506    V165507 V165508 V165509 V165510 V165511 V165512 V165513 V165514 V165515 V165516 V165517 V165518
    V165519 V165520 V165521 V165522 V165523 V165524 V165525 V165526 V165527 V165528 V165529 V165530    V165531 V165532 V165533 V165534 V165535 V165536 V165537 V165538 V165539 V165540 V165541 V165542
    V165543 V165544 V165545 V165546 V165547 V165548 V165549 V165550 V165551 V165552 V165553 V165554    V165555 V165556 V165557 V165558 V165559 V165560 V165561 V165562 V165563 V165564 V165565 V165566
    V165567 V165568 V165569 V165570 V165571 V165572 V165573 V165574 V165575 V165576 V165577 V165578    V165579 V165580 V165581 V165582 V165583 V165584 V165585 V165586 V165587 V165588 V165589 V165590
    V165591 V165592 V165593 V165594 V165595 V165596 V165597 V165598 V165599 V165600 V165601 V165602    V165603 V165604 V165605 V165606 V165607 V165608 V165609 V165700 V165701 V165702 V165703 V165704
    V165705 V165706 V165707 V165708 V165709 V165710 V165711 V165712 V165713 V165714 V165715 V165716    V165717 V165718 V165719 V165720 V165721 V165722 V165723 V165724 V165725 V165726 V165727 V165728
    V165729 V165730 V165731 V165732 V165733 V165734 V165735 V165736 V165737 V165738 V165739 V165740    V165741 V165742 V165743 V165744 V165745 V165746 V165747 V165748 V165749 V165750 V165751 V165752
    V165753 V165754 V165755 V165756 V165757 V165758 V165759 V165760 V165761 V165762 V165763 V165764    V165765 V165766 V165767 V165768 V165769 V165770 V165771 V165772 V165773 V165774 V165775 V165776
    V165777 V165778 V165779 V165780 V165781 V165782 V165783 V165784 V165785 V165786 V165787 V165788    V165789 V165790 V165791 V165792 V165793 V165794 V165795 V165796 V165797 V165798 V165799 V165800
    V165801 V165802 V165803 V165804 V165805 V165806 V165807 V165808 V165809 V165810 V166001 V166002    V166003 V166004 V166005 V166006 V166007 V166008 V166009 V166010 V166011 V166012 V166013 V166014
    V166015 V166016 V166017 V166018 V166019 V166020 V166021 V166022 V166023 V166024 V166025 V166026    V166027 V166028 V166029 V166030 V166031 V166032 V166033 V166034 V166035 V166036 V166037 V166038
    V166039 V166040 V166041 V166042 V166043 V166044 V166045 V166046 V166047 V166048 V166049 V166050    V166051 V166052 V166053 V166054 V166055 V166056 V166057 V166058 V166059 V166060 V166061 V166062
    V166063 V166064 V166065 V166066 V166067 V166068 V166069 V166070 V166071 V166072 V166073 V166074    V166075 V166076 V166077 V166078 V166079 V166080 V166081 V166082 V166083 V166084 V166085 V166086
    V166087 V166088 V166089 V166090 V166091 V166092 V166093 V166094 V166095 V166096 V166097 V166098    V166099 V166100 V166101 V166102 V166103 V166104 V166105 V166106 V166107 V166108 V166109 V166110
    V166111 V166112 V166113 V166114 V166115 V166116 V166117 V166118 V166119 V166120 V166121 V166122    V166123 V166124 V166125 V166126 V166127 V166128 V166129 V166130 V166131 V166132 V166133 V166134
    V166135 V166136 V166137 V166138 V166139 V166140 V166141 V166142 V166143 V166144 V166145 V166146    V166147 V166148 V166149 V166150 V166151 V166152 V166153 V166154 V166155 V166156 V166157 V166158
    V166159 V166160 V166161 V166162 V166163 V166164 V166165 V166166 V166167 V166168 V166169 V166170    V166171 V166172 V166173 V166174 V166175 V166176 V166177 V166178 V166179 V166180 V166181 V166182
    V166183 V166184 V166185 V166186 V166187 V166188 V166189 V166190 V166191 V166192 V166193 V166194    V166195 V166196 V166197 V166198 V166199 V166200 V166201 V166202 V166203 V166204 V166205 V166206
    V166207 V166208 V166209 V166210 V166211 V166212 V166213 V166214 V166215 V166216 V166217 V166218    V166219 V166220 V166221 V166222 V166223 V166224 V166225 V166226 V166227 V166228 V166229 V166230
    V166231 V167500 V167501 V167502 V167503 V167504 V167505 V167506 V167507 V167508 V167509 V167510    V167511 V167512 V167513 V167514 V167515 V167516 V167517 V167518 V167519 V167520 V167521 V167522
    V167523 V167524 V167525 V167526 V167527 V167528 V167529 V167530 V167531 V167532 V167533 V167534    V167535 V167536 V167537 V167538 V167539 V167540 V167541 V167542 V167543 V167544 V167545 V167546
    V167547 V167548 V167549 V167550 V167551 V167552 V167553 V167554 V167555 V167556 V167557 V167558    V168000 V168001 V168002 V168003 V168004 V168005 V168006 V168007 V168008 V168009 V168010 V168011
    V168012 V168013 V168014 V168015 V168016 V168017 V168018 V168019 V168020 V168021 V168022 V168023    V168024 V168025 V168026 V168027 V168028 V168029 V168030 V168031 V168032 V168033 V168034 V168035
    V168036 V168037 V168038 V168039 V168040 V168100 V168101 V168102 V168103 V168104 V168105 V168106    V168107 V168108 V168109 V168110 V168111 V168112 V168113 V168114 V168115 V168116 V168117 V168118
    V168119 V168120 V168121 V168122 V168123 V168124 V168125 V168126 V168127 V168128 V168129 V168130    V168131 V168132 V168250 V168251 V168252 V168253 V168254 V168255 V168256 V168257 V168258 V168259
    V168260 V168261 V168262 V168263 V168264 V168265 V168266 V168300 V168301 V168302 V168303 V168304    V168305 V168306 V168307 V168308 V168309 V168310 V168311 V168312 V168313 V168314 V168315 V168316
    V168500 V168501 V168502 V168503 V168504 V168505 V168506 V168507 V168508 V168509 V168510 V168511    V168512 V168513 V168514 V168515 V168516 V168517 V168518 V168519 V168520 V168521 V168522 V168523
    V168524 V168525 V168526 V168527 V168528 Year
  /COMPRESSED.

DATASET CLOSE DataSet4.
EXE.

GET
  FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 Analysis/anes_timeseries_2016_truncated for merge.sav'.
DATASET NAME DataSet5 WINDOW=FRONT.

DATASET ACTIVATE DataSet1.
STAR JOIN
  /SELECT *
  /FROM * AS t0
  /JOIN 'DataSet5' AS t1
    ON t0.VCF0006a=t1.VCF0006a
  /OUTFILE FILE=*.

DATASET CLOSE DataSet5.
EXE.

DESCRIPTIVES VCF0006a V161361x V164006 V161326 V161328 V161327.
EXECUTE.

*INTERNET - V161326 dem2_inethome

Freq V161326 dem2_inethome.
COMPUTE InternetAtHome = V161326.
IF (ProfessionalRespondents=1) InternetAtHome = dem2_inethome.
Freq InternetAtHome.
MISSING VALUES InternetAtHome (-9,-8).
RECODE InternetAtHome (1=1) (2=0).
VALUE LABELS 
InternetAtHome 
0 'No Internet'
1 'Internet at Home'.
Freq InternetAtHome.

*PHONE - V161328 V161327 dem2_landline dem2_cellnum

Freq V161328 V161327 dem2_landline dem2_cellnum.

RECODE dem2_landline (0=0) (1 THRU HI =1) INTO Landline.
RECODE dem2_cellnum (0=0) (1 THRU HI =1) INTO Cell.
Freq Landline Cell.
IF (Landline =1 AND Cell=0) LC = 1.
IF (Landline =0 AND Cell=1) LC = 2.
IF (Landline =1 AND Cell=1) LC = 3.
Freq LC.
COMPUTE LandlineCell = V161327.
IF (ProfessionalRespondents=1) LandlineCell = LC.
MISSING VALUES LandlineCell (-9,-8).
VALUE LABELS
LandlineCell
1 'Only Landline'
2 'Only Cell'
3 'Both Landline and Cell'.
Freq LandlineCell.
RECODE LandlineCell (1=1) (2=0) (3=0) INTO LCLand.
RECODE LandlineCell (1=0) (2=1) (3=0) INTO LCCell.
RECODE LandlineCell (1=0) (2=0) (3=1) INTO LCBoth.
Freq LCLand LCCell LCBoth. 

SAVE OUTFILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 '+
    'Analysis/anes_timeseries_cdf2012_2016_Analysis File.sav'
  /COMPRESSED.

**FINAL DATA CLEANING

GET
  FILE='/Users/Alex/Dropbox/Dissertation.2/Number of Surveys/Data/2012:2016 Analysis/anes_timeseries_cdf2012_2016_Analysis File.sav'.
DATASET NAME DataSet10 WINDOW=FRONT.

DELETE VARIABLES FullWgt.
EXECUTE.

DESCRIPTIVES
VCF0009x VCF0010x VCF0011x
VCF0009y VCF0010y VCF0011y 
VCF0009z VCF0010z VCF0011z.

MEANS VCF0009x
VCF0010x
VCF0011x
VCF0009y
VCF0010y
VCF0011y 
VCF0009z
VCF0010z
VCF0011z BY ModeYear.

Freq ModeYear.
COMPUTE FullWgt = -1.
IF (ModeYear = 1) FullWgt = VCF0009y.
IF (ModeYear = 2) FullWgt = VCF0009y.
IF (ModeYear = 3) FullWgt = VCF0009x.
IF (ModeYear = 4) FullWgt = VCF0009x.
MEANS FullWgt BY ModeYear.

WEIGHT BY FullWgt.
EXE.

Freq Year2016.
RECODE Year2016 (1=0) (0=1) INTO Year2012.
CROSS Year2016 BY Year2012.

Freq WebMode.
COMPUTE Year2012WebInt = WebMode * Year2012.

CROSS Year2016Treatment BY Year2012WebInt.
CROSS Year2012WebInt BY Year2012.

Freq Year2012 Webmode Year2012WebInt.

Freq LandlineCell.
RECODE LandlineCell (1=1) (2=0) (3=1) INTO AnyLandline.
Freq AnyLandline.
CROSS AnyLandline BY ModeYear
    /cells=col count.

Freq Income.
CROSS Income BY ModeYear
    /cells=col count.

Freq InternetAtHome.
CROSS InternetAtHome BY ModeYear
    /cells=col count.


*********************TABLE 7 - DEMOGRAPHIC FREQUENCIES FOR 2012/2016-MODE COMPARISON

*FEMALE

ONEWAY Female BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*AGE

ONEWAY Age18 BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Age31 BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Age46 BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Age61 BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*MARITAL STATUS

ONEWAY Married BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*EDUCATION

ONEWAY EducLTHS BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY EducHS BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY EducSomeC BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY EducBA BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY EducGrad BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*WORK STATUS

ONEWAY Working BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*RACE/ETHNICITY

ONEWAY Black BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Asian BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Hispanic BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY White BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*INTERNET AT HOME

ONEWAY InternetAtHome BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*PHONE

ONEWAY LCLand BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY LCCell BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY LCBoth BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).


*INCOME

ONEWAY Inc0 BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Inc30 BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Inc60 BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Inc100 BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*PARTISANSHIP

ONEWAY Democrat BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Independent BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Republican BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*IDEOLOGY

ONEWAY Liberal BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Moderate BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY Conservative BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY NoThoughtIdeology BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*INTEREST

Freq Interest.

ONEWAY INTNotMuch BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY IntSomewhat BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

ONEWAY IntVery BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

*********************TABLE 8 - LOGISTIC REGRESSION OF SPEEDERS

**SPEEDERS

*MEDIAN TIME - 
*WEB - 2012 - 83 (41.5) - 2016=68.5 (34.25); 
*FTF - 2012 - 94.7 (47.35) - 2016=74.2 (37.1); 

MEANS SurveyDuration BY ModeYear
    /cells=med.

DESCRIPTIVES SurveyDuration.
COMPUTE Speeders =0.
IF SYSMIS(SurveyDuration) Speeders=-9.
IF (ModeYear=1 and SurveyDuration LE 41.5) Speeders=1.
IF (ModeYear=2 and SurveyDuration LE 34.25) Speeders=1.
IF (ModeYear=3 and SurveyDuration LE 47.35) Speeders=1.
IF (ModeYear=4 and SurveyDuration LE 37.1) Speeders=1.
Freq Speeders.

MEANS Speeders BY ModeYear.

ONEWAY Speeders BY ModeYear
  /STATISTICS DESCRIPTIVES
  /MISSING ANALYSIS
  /POSTHOC=BONFERRONI ALPHA(0.05).

TEMP.
SELECT IF (WebMode=1).
LOGISTIC REGRESSION VARIABLES Speeders
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income   
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).


*********************TABLE 9 - NON-DIFFERENTIATION MODELS

*THERMS - GROUPS

Freq  VCF0206 VCF0207 VCF0209 VCF0210 VCF0211 VCF0212 VCF0217 VCF0218 
VCF0223 VCF0224 VCF0227 VCF0228 VCF0232 VCF0233 VCF0234 VCF0253.
COMPUTE nd5a = VCF0206.
COMPUTE nd5b = VCF0207.
COMPUTE nd5c = VCF0209.
COMPUTE nd5d =      VCF0210.
COMPUTE nd5e =      VCF0211.
COMPUTE nd5f =      VCF0212.
COMPUTE nd5g =      VCF0217.
COMPUTE nd5h =      VCF0218.
COMPUTE nd5i =      VCF0223.
COMPUTE nd5j =      VCF0224.
COMPUTE nd5k =      VCF0227.
COMPUTE nd5l =      VCF0228.
COMPUTE nd5m =      VCF0232.
COMPUTE nd5n =      VCF0233.
COMPUTE nd5o =      VCF0234.
COMPUTE nd5p =      VCF0253.

DESCRIPTIVES 
nd5a nd5b nd5c nd5d nd5e
nd5f nd5g nd5h nd5i nd5j
nd5k nd5l nd5m  nd5n nd5o
nd5p.

COMPUTE nd5therms = 
(
(sqrt(abs(nd5a - nd5b))) + 
(sqrt(abs(nd5a - nd5c))) + 
(sqrt(abs(nd5a - nd5d))) + 
(sqrt(abs(nd5a - nd5e))) + 
(sqrt(abs(nd5a - nd5f))) + 
(sqrt(abs(nd5a - nd5g))) + 
(sqrt(abs(nd5a - nd5h))) + 
(sqrt(abs(nd5a - nd5i))) + 
(sqrt(abs(nd5a - nd5j))) + 
(sqrt(abs(nd5a - nd5k))) + 
(sqrt(abs(nd5a - nd5l))) + 
(sqrt(abs(nd5a - nd5m))) + 
(sqrt(abs(nd5a - nd5n))) + 
(sqrt(abs(nd5a - nd5o))) + 
(sqrt(abs(nd5a - nd5p))) + 
(sqrt(abs(nd5b - nd5c))) + 
(sqrt(abs(nd5b - nd5d))) + 
(sqrt(abs(nd5b - nd5e))) + 
(sqrt(abs(nd5b - nd5f))) + 
(sqrt(abs(nd5b - nd5g))) + 
(sqrt(abs(nd5b - nd5h))) + 
(sqrt(abs(nd5b - nd5i))) + 
(sqrt(abs(nd5b - nd5j))) + 
(sqrt(abs(nd5b - nd5k))) + 
(sqrt(abs(nd5b - nd5l))) + 
(sqrt(abs(nd5b - nd5m))) + 
(sqrt(abs(nd5b - nd5n))) + 
(sqrt(abs(nd5b - nd5o))) + 
(sqrt(abs(nd5b - nd5p))) + 
(sqrt(abs(nd5c - nd5d))) +
(sqrt(abs(nd5c - nd5e))) +
(sqrt(abs(nd5c - nd5f))) +
(sqrt(abs(nd5c - nd5g))) +
(sqrt(abs(nd5c - nd5h))) +
(sqrt(abs(nd5c - nd5i))) + 
(sqrt(abs(nd5c - nd5j))) + 
(sqrt(abs(nd5c - nd5k))) + 
(sqrt(abs(nd5c - nd5l))) + 
(sqrt(abs(nd5c - nd5m))) + 
(sqrt(abs(nd5c - nd5n))) + 
(sqrt(abs(nd5c - nd5o))) + 
(sqrt(abs(nd5c - nd5p))) + 
(sqrt(abs(nd5d - nd5e))) +
(sqrt(abs(nd5d - nd5f))) +
(sqrt(abs(nd5d - nd5g))) +
(sqrt(abs(nd5d - nd5h))) +
(sqrt(abs(nd5d - nd5i))) + 
(sqrt(abs(nd5d - nd5j))) + 
(sqrt(abs(nd5d - nd5k))) + 
(sqrt(abs(nd5d - nd5l))) + 
(sqrt(abs(nd5d - nd5m))) + 
(sqrt(abs(nd5d - nd5n))) + 
(sqrt(abs(nd5d - nd5o))) + 
(sqrt(abs(nd5d - nd5p))) + 
(sqrt(abs(nd5e - nd5f))) +
(sqrt(abs(nd5e - nd5g))) +
(sqrt(abs(nd5e - nd5h))) +
(sqrt(abs(nd5e - nd5i))) + 
(sqrt(abs(nd5e - nd5j))) + 
(sqrt(abs(nd5e - nd5k))) + 
(sqrt(abs(nd5e - nd5l))) + 
(sqrt(abs(nd5e - nd5m))) + 
(sqrt(abs(nd5e - nd5n))) + 
(sqrt(abs(nd5e - nd5o))) + 
(sqrt(abs(nd5e - nd5p))) + 
(sqrt(abs(nd5f - nd5g))) +
(sqrt(abs(nd5f - nd5h))) +
(sqrt(abs(nd5f - nd5i))) + 
(sqrt(abs(nd5f - nd5j))) + 
(sqrt(abs(nd5f - nd5k))) + 
(sqrt(abs(nd5f - nd5l))) + 
(sqrt(abs(nd5f - nd5m))) + 
(sqrt(abs(nd5f - nd5n))) + 
(sqrt(abs(nd5f - nd5o))) + 
(sqrt(abs(nd5f - nd5p))) + 
(sqrt(abs(nd5g - nd5h))) +
(sqrt(abs(nd5g - nd5i))) + 
(sqrt(abs(nd5g - nd5j))) + 
(sqrt(abs(nd5g - nd5k))) + 
(sqrt(abs(nd5g - nd5l))) + 
(sqrt(abs(nd5g - nd5m))) + 
(sqrt(abs(nd5g - nd5n))) + 
(sqrt(abs(nd5g - nd5o))) + 
(sqrt(abs(nd5g - nd5p))) + 
(sqrt(abs(nd5h - nd5i))) + 
(sqrt(abs(nd5h - nd5j))) + 
(sqrt(abs(nd5h - nd5k))) + 
(sqrt(abs(nd5h - nd5l))) + 
(sqrt(abs(nd5h - nd5m))) + 
(sqrt(abs(nd5h - nd5n))) + 
(sqrt(abs(nd5h - nd5o))) + 
(sqrt(abs(nd5h - nd5p))) + 
(sqrt(abs(nd5i - nd5j))) + 
(sqrt(abs(nd5i - nd5k))) + 
(sqrt(abs(nd5i - nd5l))) + 
(sqrt(abs(nd5i - nd5m))) + 
(sqrt(abs(nd5i - nd5n))) + 
(sqrt(abs(nd5i - nd5o))) + 
(sqrt(abs(nd5i - nd5p))) + 
(sqrt(abs(nd5j - nd5k))) + 
(sqrt(abs(nd5j - nd5l))) + 
(sqrt(abs(nd5j - nd5m))) + 
(sqrt(abs(nd5j - nd5n))) + 
(sqrt(abs(nd5j - nd5o))) + 
(sqrt(abs(nd5j - nd5p))) + 
(sqrt(abs(nd5k - nd5l))) + 
(sqrt(abs(nd5k - nd5m))) + 
(sqrt(abs(nd5k - nd5n))) + 
(sqrt(abs(nd5k - nd5o))) + 
(sqrt(abs(nd5k - nd5p))) + 
(sqrt(abs(nd5l - nd5m))) + 
(sqrt(abs(nd5l - nd5n))) + 
(sqrt(abs(nd5l - nd5o))) + 
(sqrt(abs(nd5l - nd5p))) + 
(sqrt(abs(nd5m - nd5n))) + 
(sqrt(abs(nd5m - nd5o))) + 
(sqrt(abs(nd5m - nd5p))) + 
(sqrt(abs(nd5o - nd5o))) + 
(sqrt(abs(nd5o - nd5p))) 
/16).

DESCRIPTIVES nd5therms.
COMPUTE STDnd5therms = abs(1- (nd5therms/721.1)).
DESCRIPTIVES STDnd5therms.

MEANS STDnd5therms BY ModeYear.

*CANDIDATE AFFECTS

Freq VCF0358 VCF0359 VCF0360 VCF0361 VCF0370 VCF0371 VCF0372 VCF0373.
RECODE VCF0358 VCF0359 VCF0360 VCF0361 VCF0370 VCF0371 VCF0372 VCF0373 (1=1) (2=0) INTO 
DA1 DA2 DA3 DA4 RA1 RA2 RA3 RA4.
Freq DA1 DA2 DA3 DA4 RA1 RA2 RA3 RA4.

COMPUTE nd11a = DA1.
COMPUTE nd11b = DA2.
COMPUTE nd11c = DA3.
COMPUTE nd11d =      DA4.
DESCRIPTIVES nd11a nd11b nd11c nd11d.

COMPUTE nd11DA = 
(
(sqrt(abs(nd11a - nd11b))) + 
(sqrt(abs(nd11a - nd11c))) + 
(sqrt(abs(nd11a - nd11d))) + 
(sqrt(abs(nd11b - nd11c))) + 
(sqrt(abs(nd11b - nd11d))) + 
(sqrt(abs(nd11c - nd11d)))
/4).
DESCRIPTIVES nd11DA.
COMPUTE STDnd11DA = abs(1- (nd11DA/4)).
DESCRIPTIVES STDnd11DA.

MEANS STDnd11DA BY ModeYear.

COMPUTE nd12a = RA1.
COMPUTE nd12b = RA2.
COMPUTE nd12c = RA3.
COMPUTE nd12d =      RA4.
DESCRIPTIVES nd12a nd12b nd12c nd12d.

COMPUTE nd12RA = 
(
(sqrt(abs(nd12a - nd12b))) + 
(sqrt(abs(nd12a - nd12c))) + 
(sqrt(abs(nd12a - nd12d))) + 
(sqrt(abs(nd12b - nd12c))) + 
(sqrt(abs(nd12b - nd12d))) + 
(sqrt(abs(nd12c - nd12d)))
/4).
DESCRIPTIVES nd12RA.
COMPUTE STDnd12RA = abs(1- (nd12RA/4)).
DESCRIPTIVES STDnd12RA.

MEANS STDnd12RA BY ModeYear.

**THEMS POLITICAL FIGURES - EXCLUDING VCF0425 & VCF0427 TO INCREASE n

DESCRIPTIVES
VCF0424 VCF0426 VCF0428 VCF0450 VCF0451 VCF0471.

COMPUTE nd13a = VCF0424.
COMPUTE nd13b = VCF0426.
COMPUTE nd13c = VCF0428.
COMPUTE nd13d =      VCF0471.
DESCRIPTIVES nd13a nd13b nd13c nd13d.
Freq  nd13a nd13b nd13c nd13d.
MISSING VALUES nd13d (98,99).
DESCRIPTIVES nd13a nd13b nd13c nd13d.

COMPUTE nd13ptherms = 
(
(sqrt(abs(nd13a - nd13b))) + 
(sqrt(abs(nd13a - nd13c))) + 
(sqrt(abs(nd13a - nd13d))) + 
(sqrt(abs(nd13b - nd13c))) + 
(sqrt(abs(nd13b - nd13d))) + 
(sqrt(abs(nd13c - nd13d)))
/4).
DESCRIPTIVES nd13ptherms.
COMPUTE STDnd1ptherms = abs(1- (nd13ptherms/35.46)).
DESCRIPTIVES STDnd1ptherms.

MEANS STDnd1ptherms BY ModeYear.

***FEDERAL SPENDING

Freq VCF0888 VCF0890 VCF0894  VCF9047 VCF9048 VCF9049.
RECODE VCF0888 VCF0890 VCF0894  VCF9047 VCF9048 VCF9049 (1=3) (2=2)(3=1) INTO
FS1 FS2 FS3 FS4 FS5 FS6.
Freq FS1 FS2 FS3 FS4 FS5 FS6.

COMPUTE nd14a = FS1.
COMPUTE nd14b = FS2.
COMPUTE nd14c = FS3.
COMPUTE nd14d = FS4.
COMPUTE nd14e = FS5.
COMPUTE nd14f =  FS6.
DESCRIPTIVES nd14a nd14b nd14c nd14d nd14e nd14f.

COMPUTE nd14FS = 
(
(sqrt(abs(nd14a - nd14b))) + 
(sqrt(abs(nd14a - nd14c))) + 
(sqrt(abs(nd14a - nd14d))) + 
(sqrt(abs(nd14a - nd14e))) + 
(sqrt(abs(nd14a - nd14f))) + 
(sqrt(abs(nd14b - nd14c))) + 
(sqrt(abs(nd14b - nd14d))) + 
(sqrt(abs(nd14b - nd14e))) + 
(sqrt(abs(nd14b - nd14f))) + 
(sqrt(abs(nd14c - nd14d))) + 
(sqrt(abs(nd14c - nd14e))) + 
(sqrt(abs(nd14c - nd14f))) + 
(sqrt(abs(nd14d - nd14e))) + 
(sqrt(abs(nd14d - nd14f))) + 
(sqrt(abs(nd14e - nd14f))) 
/6).
DESCRIPTIVES nd14FS.
COMPUTE STDnd1FS = abs(1- (nd14FS/13.66)).
DESCRIPTIVES STDnd1FS.

MEANS STDnd1FS BY ModeYear.

**EGALITARIANISM

Freq  VCF9014 VCF9015 VCF9016 VCF9017 VCF9018.
RECODE   VCF9016 VCF9017 VCF9018 (1=5) (2=4)(3=3)(4=2)(5=1) INTO 
Eg1 Eg2 Eg3 .
Freq Eg1 Eg2 Eg3 .

COMPUTE nd15a = Eg1.
COMPUTE nd15b = Eg2.
COMPUTE nd15c = Eg3.
DESCRIPTIVES nd15a nd15b nd15c .

COMPUTE nd15Eg = 
(
(sqrt(abs(nd15a - nd15b))) + 
(sqrt(abs(nd15a - nd15c))) + 
(sqrt(abs(nd15b - nd15c))) 
/3).
DESCRIPTIVES nd15Eg.
COMPUTE STDnd1Eg = abs(1- (nd15Eg/4.07)).
DESCRIPTIVES STDnd1Eg.

MEANS STDnd1Eg BY ModeYear.

*RACIAL RESENTMENT

DESCRIPTIVES  VCF9040 VCF9041 VCF9042.
Freq  VCF9040 VCF9041 VCF9042.
RECODE  VCF9040 VCF9041 VCF9042 (1=5)(2=4)(3=3) (4=2)(5=1) INTO 
RR1 RR2 RR3.
Freq RR1 RR2 RR3.

COMPUTE nd16a = RR1.
COMPUTE nd16b = RR2.
COMPUTE nd16c = RR3.
DESCRIPTIVES nd16a nd16b nd16c .

COMPUTE nd16RR = 
(
(sqrt(abs(nd16a - nd16b))) + 
(sqrt(abs(nd16a - nd16c))) + 
(sqrt(abs(nd16b - nd16c))) 
/3).
DESCRIPTIVES nd16RR.
COMPUTE STDnd1RR = abs(1- (nd16RR/4.07)).
DESCRIPTIVES STDnd1RR.

MEANS STDnd1RR BY ModeYear.

**IDEOLOGY

Freq VCF0503 VCF0504 VCF0803 VCF9088 VCF9096 .
MISSING VALUES VCF0503 VCF0504 VCF0803 VCF9088 VCF9096 (0,8,9).
DESCRIPTIVES VCF0503 VCF0504 VCF0803 VCF9088 VCF9096 .

COMPUTE nd17a = VCF0503.
COMPUTE nd17b = VCF0504.
COMPUTE nd17c = VCF0803.
COMPUTE nd17d = VCF9088.
COMPUTE nd17e = VCF9096.
DESCRIPTIVES nd14a nd14b nd14c nd14d nd14e .

COMPUTE nd17Ideol = 
(
(sqrt(abs(nd17a - nd17b))) + 
(sqrt(abs(nd17a - nd17c))) + 
(sqrt(abs(nd17a - nd17d))) + 
(sqrt(abs(nd17a - nd17e))) + 
(sqrt(abs(nd17b - nd17c))) + 
(sqrt(abs(nd17b - nd17d))) + 
(sqrt(abs(nd17b - nd17e))) +
(sqrt(abs(nd17c - nd17d))) + 
(sqrt(abs(nd17c - nd17e))) + 
(sqrt(abs(nd17d - nd17e))) 
/5).
DESCRIPTIVES nd17Ideol.
COMPUTE STDnd1ideol = abs(1- (nd17Ideol/16.41)).
DESCRIPTIVES STDnd1ideol.

MEANS STDnd1ideol BY ModeYear.

*****2012/2016 FULL MODEL COMPARISON
*GROUP THERMS - STDnd5therms

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT STDnd5therms
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*POLITICAL FIGURES THERMS - STDnd1ptherms

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT STDnd1ptherms
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*DEM CAND AFFECT - STDnd11DA

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT STDnd11DA
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*REP CAND AFFECT - STDnd12RA

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT STDnd12RA
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*FEDERAL SPENDING - STDnd1FS

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT STDnd1FS
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*EGALITARIANISM - STDnd1Eg

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT STDnd1Eg
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*RACIAL RESENTMENT - STDnd1RR

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT STDnd1RR
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*IDEOLOGY - STDnd1ideol

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT STDnd1ideol
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.


**SUBTANTIVE VARIABLES

*PRES APPROVAL.
Freq VCF0450 VCF0451.
MISSING VALUES VCF0451 (0, 8).
RECODE VCF0451 (1=4)(2=3)(3=2)(4=1) INTO PresApproval.
Freq PresApproval.
MEANS PresApproval  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT PresApproval
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income   
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT PresApproval
  /METHOD=ENTER Year2012WebInt Year2012 Webmode       
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*PRES APPR ON ECONOMY.
Freq VCF9009.
RECODE VCF9009 (1=4) (2=3)(4=2)(5=1) INTO PresAppEcon.
Freq PresAppEcon.
MEANS PresAppEcon  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT PresAppEcon
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT PresAppEcon
  /METHOD=ENTER Year2012WebInt Year2012 Webmode        
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.


*GOV RESPONSIVENESS.
Freq VCF0649.
MISSING VALUES VCF0649 (999).
RECODE VCF0649 (0=1) (50=2)(100=3) INTO GovResp.
Freq GovResp.
MEANS GovResp  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT GovResp
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT GovResp
  /METHOD=ENTER Year2012WebInt Year2012 Webmode         
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*TRUST INDEX.
Freq VCF0656.
MEANS VCF0656  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT VCF0656
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT VCF0656
  /METHOD=ENTER Year2012WebInt Year2012 Webmode      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.


*RACIAL RESENTMENT.
Freq VCF9040 VCF9041 VCF9042.
CORR VCF9040 VCF9041 VCF9042.
MISSING VALUES VCF9040 VCF9041 VCF9042 (8,9).
RECODE VCF9040 VCF9041 VCF9042 (1=5)(2=4)(3=3)(4=2)(5=1) INTO RRSpecialTreat RRTryHarder RRLTDeserve.
Freq RRSpecialTreat RRTryHarder RRLTDeserve.

*BLACKS SHOULD NOT HAVE SPECIAL FAVORS.
MEANS RRSpecialTreat  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT RRSpecialTreat
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT RRSpecialTreat
  /METHOD=ENTER Year2012WebInt Year2012 Webmode         
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*BLACKS MUST TRY HARDER TO SUCCEED.
MEANS  RRTryHarder BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT RRTryHarder
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT RRTryHarder
  /METHOD=ENTER Year2012WebInt Year2012 Webmode       
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*BLACKS GOTTEN LESS THAN THEY DESERVE.
MEANS  RRLTDeserve BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT RRLTDeserve
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT RRLTDeserve
  /METHOD=ENTER Year2012WebInt Year2012 Webmode          
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

**DISCUSS POLITICS.
Freq VCF0731.
RECODE VCF0731 (1=1) (5=0) INTO DiscussPolitics.
Freq DiscussPolitics.
MEANS DiscussPolitics  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
LOGISTIC REGRESSION VARIABLES DiscussPolitics
  /METHOD=ENTER  Year2012      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).

LOGISTIC REGRESSION VARIABLES DiscussPolitics
  /METHOD=ENTER  Year2012WebInt Year2012 Webmode          
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).

*DISCUSS OFTEN.
Freq VCF0733.
MISSING VALUES VCF0733 (9).
EXE.
MEANS VCF0733  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT VCF0733
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT VCF0733
  /METHOD=ENTER Year2012WebInt Year2012 Webmode        
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*EXTERNAL EFFICACY INDEX.
Freq VCF0648.
RECODE VCF0648 (0=1) (25=2)(50=3)(75=4)(100=5) INTO ExtEfficacy.
Freq ExtEfficacy.
MEANS ExtEfficacy  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT ExtEfficacy
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT ExtEfficacy
  /METHOD=ENTER Year2012WebInt Year2012 Webmode          
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*ECONOMY LAST YEAR.
Freq  VCF0871.
RECODE VCF0871 (1=5)(2=4)(3=3)(4=2)(5=1) INTO EconLastYear.
Freq EconLastYear.
MEANS EconLastYear  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT EconLastYear
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT EconLastYear
  /METHOD=ENTER Year2012WebInt Year2012 Webmode         
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*ECONOMY NEXT YEAR.
Freq VCF0872.
RECODE VCF0872 (1=3)(3=2)(5=1) INTO EconFuture.
Freq EconFuture.
MEANS EconFuture  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT EconFuture
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT EconFuture
  /METHOD=ENTER Year2012WebInt Year2012 Webmode        
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*FEDERAL ISSUES.
Freq VCF0888 VCF0890 VCF0894 VCF9047 VCF9048 VCF9049.
RECODE VCF0888 VCF0890 VCF0894 VCF9047 VCF9048 VCF9049 (1=3)(2=2)(3=1)
 INTO FedCrime FedSchool FedWelfare FedEnvir FedScience FedSocialSec.
Freq FedCrime FedSchool FedWelfare FedEnvir FedScience FedSocialSec.

*CRIME.
MEANS FedCrime  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedCrime
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedCrime
  /METHOD=ENTER Year2012WebInt Year2012 Webmode       
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*SCHOOL.
MEANS FedSchool  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedSchool
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedSchool
  /METHOD=ENTER Year2012WebInt Year2012 Webmode        
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*WELFARE.
MEANS FedWelfare  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedWelfare
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedWelfare
  /METHOD=ENTER Year2012WebInt Year2012 Webmode           
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*ENVIRONMENT.
MEANS FedEnvir  BY ModeYear.
 
TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedEnvir
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedEnvir
  /METHOD=ENTER Year2012WebInt Year2012 Webmode      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*SCIENCE .
MEANS  FedScience BY ModeYear.
 
TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedScience
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedScience
  /METHOD=ENTER Year2012WebInt Year2012 Webmode        
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

*SOCIAL SECUTIRY .
MEANS FedSocialSec  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedSocialSec
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT FedSocialSec
  /METHOD=ENTER Year2012WebInt Year2012 Webmode        
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

**CONGRESS APPROVAL.
Freq  VCF0992.
RECODE VCF0992 (1=1)(5=0) INTO CongressApp.
Freq CongressApp.
MEANS CongressApp  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
LOGISTIC REGRESSION VARIABLES CongressApp
  /METHOD=ENTER  Year2012      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).

LOGISTIC REGRESSION VARIABLES CongressApp
  /METHOD=ENTER  Year2012WebInt Year2012 Webmode      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).


*POLITICAL KNOWLEDGE.

*HOUSE MAJORITY.
Freq VCF0729.
RECODE VCF0729 (1=0) (2=1) INTO PKHouseMaj.
Freq PKHouseMaj.
MEANS PKHouseMaj BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
LOGISTIC REGRESSION VARIABLES PKHouseMaj
  /METHOD=ENTER  Year2012      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).

LOGISTIC REGRESSION VARIABLES PKHouseMaj
  /METHOD=ENTER  Year2012WebInt Year2012 Webmode      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).

*PARTY CONSERVATIVE.
Freq PKPartyConservative.
MEANS PKPartyConservative BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
LOGISTIC REGRESSION VARIABLES PKPartyConservative
  /METHOD=ENTER  Year2012      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).

LOGISTIC REGRESSION VARIABLES PKPartyConservative
  /METHOD=ENTER  Year2012WebInt Year2012 Webmode      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).

*WORD COUNTS

Freq WordSumCount.
MEANS WordSumCount  BY ModeYear.

TEMP.
SELECT IF (WebMode=1).
REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT WordSumCount
  /METHOD=ENTER Year2012     
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA  TOL
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT WordSumCount
  /METHOD=ENTER Year2012WebInt Year2012 Webmode      
Female AgeCats Married Educ Working White InternetAtHome AnyLandline Income    
Independent Republican  Moderate Conservative NoThoughtIdeology.


